New decision support tools for forest tactical and operational planning

Doutoramento em Engenharia Florestal e dos Recursos Florestais - Instituto Superior de AgronomiaThe economic importance of the forest resources and the Portuguese forest-based industries motivated several studies over the last 15 years, particularly on strategic forest planning. This thesis focuses on the forest planning processes at tactical and operational level (FTOP). These problems relate to harvesting, transportation, storing, and delivering the forest products to the mills. Innovative Operation Research methods and Decision Support Systems (DSS) were developed to address some of these problems that are prevalent in Portugal. Specifically, Study I integrates harvest scheduling, pulpwood assortment, and assignment decisions at tactical level. The solution method was based in problem decomposition, combining heuristics and mathematical programming algorithms. Study II presents a solution approach based on Revenue Management principles for the reception of Raw Materials. This operational problem avoids truck congestion during the operation of pulpwood delivery. Study III uses Enterprise Architecture to design a DSS for integrating the operations performed over the pulpwood supply chain. Study IV tests this approach on a toolbox that handled the complexity of the interactions among the agents engaged on forest planning at regional level. Study V proposes an innovative technological framework that combines forest planning with forest operations' control

An integrated planning model for multi-supplier, multi-facility, multi-customer, multi-product and multi-period : application to the wood furniture industry

Typiquement, un réseau de création de valeur dans l'industrie du meuble en bois, est composé de fournisseurs de billes de bois, de scieries, de séchoirs, d'usines de meubles, de centres de distribution et de détaillants. Dans cette thèse, nous nous concentrons sur l'étude du réseau qui assure l'approvisionnement des usines de meubles en bois. La problématique à laquelle font face les entreprises de ce réseau se situe principalement au niveau de la synchronisation des flux de matière. Ces derniers doivent respecter les contraintes de capacité, de procédés, de transport et la diversité des produits, pour satisfaire la demande. La planification, dans ce contexte, repose sur une vision locale ce qui affecte la performance globale du réseau. L'objectif de cette thèse est de proposer un modèle de planification intégrée dans un contexte, multifoumisseurs, multiusines, multiproduits, multiclients et multipériodes, qui vise la synchronisation des flux, et la maximisation de la performance globale tout en respectant les différentes contraintes du réseau. Nous proposons un modèle générique du problème de planification intégrée qui permet de déterminer les décisions tactiques d'approvisionnement, d'inventaire, de flux de matière et de sous-traitance. Ce modèle est un programme linéaire mixte en nombres entiers de grande taille. Nous avons développé une heuristique basée sur la décomposition dans le temps qui exploite l'aspect multipériodes du problème de planification. Nous avons aussi proposé deux solutions basées sur la décomposition de Benders et la décomposition croisée pour réduire le temps de résolution. Enfin, ce modèle a été validé en utilisant les données réelles de l'entreprise partenaire du projet et les résultats, montrent des réductions potentielles du coût total des opérations de l'ordre de 22%. L'approche de planification intégrée adoptée ainsi que les méthodes de résolution proposées dans cette thèse peuvent être exploitées pour la planification des réseaux dans d'autres secteurs d'activités ayant des similarités avec la problématique traitée dans cette thèse

Inter-firm collaboration in transportation

Dans la littérature académique et professionnelle relative au transport de marchandise, il y a longtemps que les méthodes de planification avancées ont été identifiées comme un moyen de dégager des économies grâce à une efficacité accrue des opérations de transport. Plus récemment, la collaboration interentreprises dans la planification du transport a été étudiée comme une source de gain supplémentaire en efficacité et, par conséquent, une opportunité pour dégager de nouvelles économies pour les collaborateurs. Cependant, la mise en œuvre d'une collaboration interentreprises en transports soulève un certain nombre d’enjeux. Cette thèse aborde trois thèmes centraux de la collaboration interentreprises et démontre les contributions via des études de cas dans l’industrie forestière et du meuble. Premièrement, les moyens technologiques pour soutenir une collaboration en planification du transport sont étudiés. Un système d’aide à la décision supportant la collaboration en transport forestier est présenté. Deuxièmement, le partage entre les collaborateurs du coût commun en transport est étudié. Une méthode de répartition du coût de transport tenant compte de l'impact - l’augmentation du coût de transport - des exigences inégales entre des collaborateurs est proposée. Troisièmement, la création de groupes collaboratifs - des coalitions - dans un ensemble de collaborateurs potentiel est étudiée. Un modèle réseau pour la formation d’une coalition selon les intérêts d’un sous-ensemble de collaborateurs adoptant ou pas un comportement opportuniste est détaillé. De plus, pour soutenir l'étude des thèmes précédents, la thèse comprend deux revues de la littérature. Premièrement, une revue sur les méthodes de planification et les systèmes d’aide à la décision en transport forestier est présenté. Deuxièmement, à travers la proposition d'un cadre pour créer et gérer une collaboration en transport et, plus généralement en logistique, une revue de travaux sur le transport et la logistique collaborative est offerte.In the academic and professional literature on freight transportation, computer-based planning methods have a long time ago been identified as a means to achieve cost reduction through enhanced transportation operations efficiency. More recently, inter-firm collaboration in transportation planning has been investigated as a means to provide further gains in efficiency and, in turn, to achieve additional cost reduction for the collaborators. However, implementation of inter-firm collaboration in transportation raises a number of issues. This thesis addresses three central themes in inter-firm collaboration and exemplifies the contributions in case studies involving collaboration in furniture and forest transportation. First, technological means to enable collaboration in transportation planning are studied. Embedding a computer-based planning method for truck routing, a decision support system enabling collaborative transportation is presented. Second, sharing the common transportation cost among collaborators is studied. A cost allocation method taking into account the impact – an increase of the transportation cost – of uneven requirements among collaborators is proposed. Third, building collaborating groups (i.e. coalitions) among a set of potential collaborators is studied. A network model for coalition formation by a subset of self-interested collaborators adopting or not an opportunistic behaviour is detailed. Moreover, to support the study of the aforementioned themes, the thesis includes two literature reviews. First, a survey on planning methods and decision support systems for vehicle routing problem in forest transportation is presented. Second, through the proposition of a framework for building and managing collaboration in transportation and, more generally in logistics, a survey of works on collaborative transportation and logistics is given

Forest Products Trucking Industry in Maine: Opportunities and Challenges

Forest transportation from in-woods to the final point of utilization is one of the major components in forest harvesting operations in terms of economics, public visibility and safety. In many cases, the price of delivered wood products depends on the transportation distance. Transportation is also crucial in terms of ensuring the supply of demanded products on time. Globally, road transportation being the most predominant medium for forest products transportation, majority of research are focused on this subject. These scientific researches are of diverse nature; with main emphasis on improving the supply chain issues and minimizing cost of transportation, including road construction and maintenance. However, the scientific research focusing on overall challenges faced by forest transportation sector and their potential resolutions is scant. The aim of this study was to document and evaluate the problems associated with the forest tucking sector of Maine. The next objective was to validate potential solutions, obtained through literature, with the stakeholders in the state. The third objective was to develop a management guideline. The first step was an extensive scientific literature search related to secondary forest products transportation. A total of 131 scientific articles published from year 2000 to 2015 were collected and categorized into six different research themes. This helped in better understanding of the current trends and advances in the field. Supply chain issues and roads were the most studied research themes in this field; while trucking efficiency and safety bottomed the list. Followed by which, a cross sectional survey was carried out in a conference setting to document and rank the major challenges to the forest trucking sector in the state. The specific reasons behind the prevalence of those challenges were also discussed. The survey yielded 31.22% response rate and the major challenge for the state was regarded as availability of market and lack of skilled manpower. These challenges were also compared with the situation of other regions in the nation and world through literature and trade magazine analysis. For developing a management guideline with validated resolutions for the trucking related problems, a qualitative case study method with semi-structured interviews was implemented. The primary intention was to understand the perspectives of stakeholders on field level solutions. The stakeholders included forest managers, personnel from professional forestry societies, and trucking & logging contractors. Thirteen interviews were conducted, with each being audio recorded and later transcribed verbatim. The presented results included various solutions for specific problems related to trucking in Maine from stakeholders’ perspective. The key findings of this process also serve as a management guideline for forest trucking industry of Maine. This study is expected to support the understanding of challenges in general and fill the gap of knowledge regarding trucking in Maine. Land owning and managing, trucking, and logging companies would be able to use the results from this study to prepare trucking plans to support logistics based on given circumstances. These findings can be used as a baseline figure for future studies involving supply chain analysis for the logging industry

Optimization-based decision support systems for planning problems in processing industries

Summary Optimization-based decision support systems for planning problems in processing industries Nowadays, efficient planning of material flows within and between supply chains is of vital importance and has become one of the most challenging problems for decision support in practice. The tremendous progress in hard- and software of the past decades was an important gateway for developing computerized systems that are able to support decision making on different levels within enterprises. The history of such systems started in 1971 when the concept of Decision Support Systems (DSS) emerged. Over the years, the field of DSS has evolved into a broad variety of directions. The described research in this thesis limits to the category of model-driven or optimization-based DSS. Simultaneously with the emergence of DSS, software vendors recognized the high potentials of available data and developed Enterprise Systems to standardize planning problems. Meanwhile, information oriented systems like MRP and its successors are extended by the basic concepts of optimization based decision support. These systems are called Advanced Planning Systems (APS). The main focus of APS is to support decision making at different stages or phases in the material flow, i.e. from procurement, production, distribution to sales (horizontal-axis), on different hierarchical aggregation levels (vertical-axis) ranging from strategic (long-term) to operational (short- term) planning. This framework of building blocks decomposes planning tasks hierarchically into partial planning problems. This basic architecture of the planning processes in APS is known as the Supply Chain Planning Matrix (SCPM). Compared to, for instance, discrete parts manufacturing, planning tasks are much more complicated in processing industries due to a natural variation in the composition of raw materials, the impact of processing operations on properties of material flows, sequence dependent change-over times, the inevitable decline in quality of product flows and relatively low margins. These specific characteristics gave rise to focus on optimization-based decision support in the domain of processing industries. The problems to be addressed in this field call for (inter-related) decisions with respect to the required raw materials, the production quantities to be manufactured, the efficient use of available resources, and the times at which raw materials must be available. Although different APS modules can interact directly, coordination and integration is often restricted to the exchange of data flows between different modules. Given the need for specific integrated decision support, the research presented in this thesis focusses particularly on medium to short term decision support at production stage in processing industry, including the vertical and horizontal integration and coordination with adjacent building blocks in the SCPM. Extensive reviews from literature show that the gap between research and practice of DSS is widening. As the field of DSS was initiated as an application oriented discipline, the strategy of what is referred to as “application-driven theory” was taken as the preferred approach for this thesis. “Application-driven” refers to a bottom-up approach which means that the relevance of the research should both be initiated and obtained from practice. The intended successful use of the proposed approaches should, where possible, be represented by tests of adequacy. Simultaneously, the contribution to “theory” aims to be a recognizable part of the research effort, i.e. obtained understanding and insights from problems in practice should provide the basis for new approaches. Based on the preceding considerations we defined the following general research objective: General research objective To support medium- to short term planning problems by optimization-based models and solution techniques such that: i) The applicability and added value of (prototype) systems is recognized and carried by decision makers in practice ii) The proposed approaches contribute to knowledge, understanding and insights from a model building and – solving point of view. In order to link the general objective with the different studies in the thesis, we defined five, recurring research premises, i.e. Professional relevance and applicability (P1), Aggregation (P2), Decomposition and reformulation (P3), Vertical integration at production level (P4), and Horizontal coordination and integration (P5). The overarching premise P1 refers to the first part of the research objective. All other premises refer to the second part of the research objective, i.e. model building and/or – solving. Several planning issues are studied to give substance to the research objective and each study is connected to at least two research premises. Study 1: Planning and scheduling in food processing industry The main question in Chapter 2 was:” How to apply aggregation, decomposition and reformulation in model-based DSS at planning and scheduling level such that the aspect of decision support is recognized and appreciated by decision makers in practice, and which level of aggregation is needed to integrate production planning (i.e. lot-sizing) and scheduling problems in a single model? The study consists of two parts. The first part of the study refers to a case study for the bottleneck packaging facilities of a large dairy company. The goal was to develop, implement and test a pilot DSS which was able to deliver solutions recognized and carried by decision makers at lower decision levels. The latter aim implied that a straight-forward aggregation on time, product type, resources or product stage, was not preferred. The key to develop an approach for regular use was to identify and take advantage of specific problem characteristics. Clustering of numerous jobs, while retaining information at order level, could be exploited in a reformulation approach. The inclusion of (combined) generalized- and variable upper bound constraints gave very tight lower bounds and sparse search trees. An extensive test phase in daily practice showed that the main benefit of the DSS was the initial quality of the generated plans including the time needed to generate these schedules. Hence, decision makers could i) postpone their planning tasks, ii) conveniently cope with rush orders or planned maintenance and iii) easily generate alternatives or revised plans when unforeseen disturbances occur. Moreover, the graphical presentation and overview of the (future) working schedule enabled order acceptance to make use of remaining capacity. The study also showed that planning problems in practice cannot be captured exhaustively by a (simplified) model. Decision makers need the opportunity to modify automatically generated plans manually and use human judgement and experience such that the solution is tuned to the actual situation. Hence, the DSS should not be considered as an optimizer but rather as a tool for generating high quality plans to be used for further analysis. Within this context the various options of a user-friendly, graphical, and fully interactive user interface, were of major importance. Although the case study clearly demonstrates the validity of earlier case based DSS research for current days APS, the proposed approach is hardly a generic solution for a complete vertical integration between lot-sizing and scheduling. If lot-size decisions are strongly affected by the sequence of jobs, production planning and scheduling should be performed simultaneously. As the described case refers to an earlier study and today’s APS do not provide modules for integrated lot-sizing and scheduling, the second part of the study gives an overview of developments in literature regarding lot-sizing and scheduling models and assess their suitability for addressing sequence-dependent setups, non-triangular setups and product decay. The review shows a tendency in which so-called Big Bucket (BB) models are currently proposed for short term time horizons too. However, we argue that segmentation of the planning horizon is a key issue for simultaneous lot-sizing and scheduling. The advantage of BB models may become a major obstacle for i) the effectiveness of simultaneous lot-sizing and scheduling, and ii) addressing specific characteristics in food processing industry. Study 2: Vertical integration of lot-sizing and scheduling in food processing industry Chapter 3 focused on a complete integration of lot-sizing and scheduling decisions in a single model. The main question was:” How to integrate production planning (i.e. lot- sizing) and scheduling problems in a single model, such that common assumptions regarding the triangular setup conditions are relaxed and issues of product decay and limited shelf lives are taken into account?” The literature research in Chapter 2 revealed that the computational advantage of time oriented aggregation in BB models may become a major obstacle in addressing the identified characteristics in FPI. In addition, product decay is primarily associated with the “age” of products and consequently relates to the segmentation of the time- horizon. Therefore, two SB models are developed to demonstrate the impact of non- triangular setups and product decay on the generated solutions. Small scale examples were used to demonstrate how a small change in the balance between inventory - and changeover costs may generate significantly different solutions, especially when the triangular setup conditions do not hold. The developed models are potentially very large formulations and, as expected, hard to solve. Exploratory research was conducted with a Relax-and-Fix (R&F) heuristic. The heuristic is based on a decomposition of the time horizon. Numerical results of small to medium sized problem instances are promising. However, solving real-size problem instances is not possible yet. Study 3: Integrated planning between procurement and production The case study in Chapter 4 focussed on the need for horizontal coordination and integration between the phases procurement and production, which is of particular importance in inter-organizational supply chains. The main question was:” How to model and solve an integrated planning problem between procurement and production, both on a mid-term and short-term planning level, in an inter-organizational supply chain? The research question was projected on an illustrative milk collection problem in practice. The aim was to develop a pilot DSS that lifted decision support for a “weaker” partner in a food supply chain to a higher level, and to illustrate the importance of horizontal integration between the phases procurement and production in an APS framework. Problem analysis revealed that the problem can be classified as an extension of the Periodic Vehicle Routing Problem (PVRP). The problem was decomposed into more tractable sub problems on different hierarchical levels, i.e. the daily (vehicle) routing problem was separated from a medium-term planning problem. On the higher planning level, numerous suppliers were aggregated such that total supply within a cluster met (multiple) vehicle loading capacities. The continuous supply of relatively small amounts from many suppliers had to be balanced with strict delivery conditions at processing level. A model was developed to assign a single (stable) collection rhythm to each cluster such that the total, weighted deviation of desired processing levels on various days in the planning horizon was minimized. The applied aggregation on the higher planning level turned out to be very beneficial for the required disaggregation at the lower planning level. Once supplier farms were geographically grouped into clusters and the aggregated supply within a cluster was assigned to a single collection rhythm with fixed collection days, the (initial) daily routing problem was considerably easier to solve for vehicle schedulers. The computational complexity of the problem was reduced by exploiting application-based properties algorithmically in a specific branch-and-bound scheme, i.e. a customized approach of Special Ordered Sets type 1 (SOS1) This approach made it possible to solve the generated problems exactly for real-size problem instances. The various facilities of a user-friendly and interactive man-machine interface (i.e. an input, planning, simulation and analysing module) turned out to be essential. Decision makers could easily change the data, and the generated plans, in a separate simulation module. However, the impact of any modification was immediately visualised by several (conflicting) indicators in the output screens, both on supply and demand level. Study 4: Mixed Integer (0-1) Fractional Programming in Paper Production Industry The study in Chapter 5 focussed on the impact of technical settings of production units on material flows. The main question was:” How to support decision-makers in practice if crucial properties of end products simultaneously depend on (endogenous) types of raw materials with different chemical or physical properties and (endogenous) technical settings of processing units? The goal of the study was to revise and upgrade an existing, locally used DSS, to a tailored and flexible tool for decision support within the enterprise. The study revealed that the aimed extension towards multi-objective decision support, together with new physical insight for calculating properties of end products due to process operations, had a substantial impact on the optimization module. The proposed solution procedure takes advantage of the problem characteristics and gives rise i) to apply and extend a classical reformulation approach for continuous linear fractional programming (FP) problems to a more general class of mixed integer (binary) FP problems and ii) to exploit the special structure between the original non- linear mixed integer model and the continuous, linear reformulation by applying the concept of Special Ordered Sets type 1 (SOS1). Although Chapter 5 focusses in particular on the reformulation and solution approach, the DSS consists of four main building blocks, i.e. the user interface, a scenario manager, a simulation- and optimization routine. The optimization module provides a powerful tool to find feasible solutions and the best (unexpected) recipes for any available set of raw materials. Moreover, it provides an innovative way of decision support for purchasing (new) pulps on the market, for assigning available pulps to different paper grades, and for attuning available stock levels of raw materials to (changing) production targets for different paper grades. The results of the optimization routine are mainly used to obtain alternative recipes for different paper grades. Usually, these recipes are stored as base scenarios and adapted to daily practice in the simulation module. Main conclusions and future research Based on the studies in the Chapters 2 and 3 we conclude that no generically applicable models and/or solution approaches exist for simultaneous planning and scheduling in processing industries. More industry-specific solutions are needed incorporating specificities of different production environments into those models. The key to develop solvable approaches for contemporary practice may be i) to use knowledge and experience from practice and take advantage of specific characteristics in different problem domains during model construction, and/or ii) to identify and exploit special problem structures for solving the related models. We conclude that surprisingly little research has been devoted to issues of coordination and integration between “procurement” and “production”. The studies in the chapters 4 and 5 confirm that sourcing of (raw) materials flows needs more attention in processing industries, particularly in push-oriented, inter-organizational networks. The valorisation of raw materials can be improved even more if the composition of raw materials is considered too in future planning problems at production level. In the second part of this thesis we focused on extensions for the applicability of Special Ordered Sets type 1 (SOS1), both from an algorithmic (Chapter 4) and modelling (Chapter 5) point of view. We conclude that the concept of SOS1 can extend a classical reformulation approach for continuous fractional programming (FP) problems, to a specific class of mixed integer (0-1) FP problems. Moreover, we conclude that a natural ordering of the variables within the sets is not necessary to make their use worthwhile. A separate (user defined) reference row or weights associated to the variables in the sets might be omitted for an efficient use of SOS1 in commercially available mathematical programming packages. However, this requires further research and extensive computational tests.</p

Exploring wood procurement system agility to improve the forest products industry’s competitiveness

Les difficultés vécus par l'industrie canadienne des produits forestiers dans la dernière décennie l’ont amené vers une transformation importante. L'innovation dans les produits et les processus est encore nécessaire afin de maximiser la valeur économique des ressources forestières. Cette thèse se concentre sur le les systèmes d'approvisionnement en bois de l’industrie forestière qui est responsable de la récolte et de la livraison des matières premières de la forêt vers les usines. Les entreprises les plus compétitives sont celles qui peuvent fournir les bons produits aux bons clients au bon moment. L'agilité du système d'approvisionnement en bois devient ainsi une des caractéristiques nécessaires à la compétitivité. Les objectifs de la thèse sont d'identifier les possibilités d'améliorer l'agilité du système d'approvisionnement en bois, de quantifier les gains potentiels et de proposer un mécanisme dans le but d’anticiper son impact à long terme. L’agilité est la capacité des systèmes d'approvisionnement en bois à répondre rapidement et efficacement à des fluctuations inattendues de la demande. Premièrement, nous identifions les capacités requises par le système d'approvisionnement en bois qui permettent l'agilité; ensuite, nous examinons la littérature portant sur les systèmes d'approvisionnement en bois pour trouver des signes de ces capacités. Suite à cette étape, une opportunité d'améliorer l'agilité des systèmes d'approvisionnement a été identifiée. Celle-ci implique une plus grande flexibilité dans le choix des traitements sylvicoles au niveau opérationnel afin de mieux aligner l'offre avec la demande. Une expérimentation a été menée en utilisant des données industrielles pour quantifier les avantages potentiels associés à l'approche. Dans les scénarios avec flexibilité permise, des profits significativement plus élevés et des taux plus élevés de satisfaction de la demande ont été observés. Ensuite, un système de simulation-optimisation de la planification hiérarchique a été développé pour étudier l'influence de la flexibilité au niveau opérationnel sur l'approvisionnement en bois à long terme. Le système a été mis en œuvre en utilisant les données hypothétiques d'une forêt du domaine public québécois pour un horizon de 100 ans. Le système développé a permis de mesurer les impacts à courts et à long terme des décisions d'approvisionnement. Il devrait permettre de mieux intégrer les pratiques d’aménagements forestiers avec les besoins de la chaîne d’approvisionnement.The significant downfall experienced by the Canadian forest products industry in the past decade has catalyzed the industry into a process of transformation. A concerted effort to maximize economic value from forest resources through innovation in both products and processes is currently underway. This thesis focuses on process innovation of wood procurement systems (WPS). WPS includes upstream processes and actors in the forest products supply chain, responsible for procuring and delivering raw materials from forests to manufacturing mills. The competitiveness of the industry depends on the agility of WPS to deliver the right product to the right customer at the right time. The specific aims of the thesis are to identify opportunities to improve wood procurement system agility, quantify the potential improvement in performance and propose a mechanism to anticipate its long-term impact. Agility is the ability to respond promptly and effectively to unexpected short-term fluctuation in demand. We first identify the capabilities a WPS needs to possess in order to enable agility; we then review the literature in the WPS domain to search for evidence of these capabilities. An opportunity to improve agility of WPS was then identified. It entailed providing managers with flexibility in the choice of silvicultural treatments at the operational level to permit better alignment of supply with the prevailing demand. An experiment was conducted using industry data to quantify the potential benefits associated with the approach. In scenarios where flexibility was permitted, significantly higher profits and demand fulfillment rates were observed. Next, a simulation-optimization system for hierarchical forest management planning was developed to examine the influence of operational level silvicultural flexibility on long-term wood supply. The system was implemented to a forest management unit in Québec in a rolling planning horizon basis for a 100 year horizon. The system demonstrated a capability to measure short and long-term impacts of supply decisions. It will prove to be a useful tool to better integrate forest management practices and supply chain needs

Transitioning to Affordable and Clean Energy

Transitioning to Affordable and Clean Energy is a collective volume which combines original contributions and review papers that address the question how the transition to clean and affordable energy can be governed. It will cover both general analyses of the governance of transition, including policy instruments, comparative studies of countries or policies, and papers setting out scientifically sound visions of a clean and just energy system. In particular, the following aspects are foregrounded: • Governing the supply and demand side transformation • Geographical and cultural differences and their consequences for the governance of energy transitions • Sustainability and justice related to energy transitions (e.g., approaches for addressing energy poverty) Transitioning to Affordable and Clean Energy is part of MDPI's new Open Access book series Transitioning to Sustainability. With this series, MDPI pursues environmentally and socially relevant research which contributes to efforts toward a sustainable world. Transitioning to Sustainability aims to add to the conversation about regional and global sustainable development according to the 17 SDGs. The book series is intended to reach beyond disciplinary, even academic boundaries

Proceedings of Abstracts, School of Physics, Engineering and Computer Science Research Conference 2022

© 2022 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Plenary by Prof. Timothy Foat, ‘Indoor dispersion at Dstl and its recent application to COVID-19 transmission’ is © Crown copyright (2022), Dstl. This material is licensed under the terms of the Open Government Licence except where otherwise stated. To view this licence, visit http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3 or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: [email protected] present proceedings record the abstracts submitted and accepted for presentation at SPECS 2022, the second edition of the School of Physics, Engineering and Computer Science Research Conference that took place online, the 12th April 2022

Optimization models and methods for real-time transportation planning in forestry

Lors du transport du bois de la forêt vers les usines, de nombreux événements imprévus peuvent se produire, événements qui perturbent les trajets prévus (par exemple, en raison des conditions météo, des feux de forêt, de la présence de nouveaux chargements, etc.). Lorsque de tels événements ne sont connus que durant un trajet, le camion qui accomplit ce trajet doit être détourné vers un chemin alternatif. En l’absence d’informations sur un tel chemin, le chauffeur du camion est susceptible de choisir un chemin alternatif inutilement long ou pire, qui est lui-même "fermé" suite à un événement imprévu. Il est donc essentiel de fournir aux chauffeurs des informations en temps réel, en particulier des suggestions de chemins alternatifs lorsqu’une route prévue s’avère impraticable. Les possibilités de recours en cas d’imprévus dépendent des caractéristiques de la chaîne logistique étudiée comme la présence de camions auto-chargeurs et la politique de gestion du transport. Nous présentons trois articles traitant de contextes d’application différents ainsi que des modèles et des méthodes de résolution adaptés à chacun des contextes. Dans le premier article, les chauffeurs de camion disposent de l’ensemble du plan hebdomadaire de la semaine en cours. Dans ce contexte, tous les efforts doivent être faits pour minimiser les changements apportés au plan initial. Bien que la flotte de camions soit homogène, il y a un ordre de priorité des chauffeurs. Les plus prioritaires obtiennent les volumes de travail les plus importants. Minimiser les changements dans leurs plans est également une priorité. Étant donné que les conséquences des événements imprévus sur le plan de transport sont essentiellement des annulations et/ou des retards de certains voyages, l’approche proposée traite d’abord l’annulation et le retard d’un seul voyage, puis elle est généralisée pour traiter des événements plus complexes. Dans cette ap- proche, nous essayons de re-planifier les voyages impactés durant la même semaine de telle sorte qu’une chargeuse soit libre au moment de l’arrivée du camion à la fois au site forestier et à l’usine. De cette façon, les voyages des autres camions ne seront pas mo- difiés. Cette approche fournit aux répartiteurs des plans alternatifs en quelques secondes. De meilleures solutions pourraient être obtenues si le répartiteur était autorisé à apporter plus de modifications au plan initial. Dans le second article, nous considérons un contexte où un seul voyage à la fois est communiqué aux chauffeurs. Le répartiteur attend jusqu’à ce que le chauffeur termine son voyage avant de lui révéler le prochain voyage. Ce contexte est plus souple et offre plus de possibilités de recours en cas d’imprévus. En plus, le problème hebdomadaire peut être divisé en des problèmes quotidiens, puisque la demande est quotidienne et les usines sont ouvertes pendant des périodes limitées durant la journée. Nous utilisons un modèle de programmation mathématique basé sur un réseau espace-temps pour réagir aux perturbations. Bien que ces dernières puissent avoir des effets différents sur le plan de transport initial, une caractéristique clé du modèle proposé est qu’il reste valable pour traiter tous les imprévus, quelle que soit leur nature. En effet, l’impact de ces événements est capturé dans le réseau espace-temps et dans les paramètres d’entrée plutôt que dans le modèle lui-même. Le modèle est résolu pour la journée en cours chaque fois qu’un événement imprévu est révélé. Dans le dernier article, la flotte de camions est hétérogène, comprenant des camions avec des chargeuses à bord. La configuration des routes de ces camions est différente de celle des camions réguliers, car ils ne doivent pas être synchronisés avec les chargeuses. Nous utilisons un modèle mathématique où les colonnes peuvent être facilement et naturellement interprétées comme des itinéraires de camions. Nous résolvons ce modèle en utilisant la génération de colonnes. Dans un premier temps, nous relaxons l’intégralité des variables de décision et nous considérons seulement un sous-ensemble des itinéraires réalisables. Les itinéraires avec un potentiel d’amélioration de la solution courante sont ajoutés au modèle de manière itérative. Un réseau espace-temps est utilisé à la fois pour représenter les impacts des événements imprévus et pour générer ces itinéraires. La solution obtenue est généralement fractionnaire et un algorithme de branch-and-price est utilisé pour trouver des solutions entières. Plusieurs scénarios de perturbation ont été développés pour tester l’approche proposée sur des études de cas provenant de l’industrie forestière canadienne et les résultats numériques sont présentés pour les trois contextes.When wood is transported from forest sites to mills, several unforeseen events may occur, events which perturb planned trips (e.g., because of weather conditions, forest fires, or the occurrence of new loads). When such events take place while the trip is under way, the truck involved must be rerouted to an alternative itinerary. Without relevant information on such alternative itineraries, the truck driver may choose a needlessly long one or, even worse, an itinerary that may itself be "closed" by an unforeseen event (the same event as for the original itinerary or another one). It is thus critical to provide drivers with real-time information, in particular, suggestions of alternative itineraries, when the planned one cannot be performed. Recourse strategies to deal with unforeseen events depend on the characteristics of the studied supply chain, such as the presence of auto-loaders and the management policy of forestry transportation companies. We present three papers dealing with three differ- ent application contexts, as well as models and solution methods adapted to each context. In the first paper, we assume a context where truck drivers are provided a priori with the whole weekly plan. In this context, every effort must be made to minimize the changes in the initial plan. Although the fleet of trucks is homogeneous, there is a priority ranking of the truck drivers. The priority drivers are ensured the highest work- loads. Minimizing the changes in their plans is also a priority. Since the consequences of unforeseen events on transportation are cancellations and/or delaying of some trips, the proposed approach deals first with single cancellations and single delayed trips and builds on these simple events to deal with more complex ones. In this approach, we try to reschedule the impacted trips within the same week in such a way that a loader is free at the truck arrival time both at the forest site and at the mill. In this way, none of the other trips will be impacted or changed. This approach provides the dispatchers with alternative plans in a few seconds. Better solutions could be found if the dispatcher is allowed to make more changes to the original plan. In the second paper, we assume a context where only one trip at a time is communicated to the drivers. The dispatcher waits until the truck finishes its trip before revealing the next trip. This context is more flexible and provides more recourse possibilities. Also, the weekly problem can be divided into daily problems since the demand is daily and the mills are open only for limited periods in the day. We use a mathematical programming model based on a time-space network representation to react to disruptions. Although the latter can have different impacts on the initial transportation plan, one key characteristic of the proposed model is that it remains valid for dealing with all the unforeseen events, regardless of their nature. Indeed, the impacts of such events are reflected in the time-space network and in the input parameters rather than in the model itself. The model is solved for the current day each time an unforeseen event is revealed. In the last paper, the fleet of trucks is heterogeneous, including trucks with onboard loaders. The route configuration of the latter is different than the regular truck routes, since they do not have to be synchronized with the loaders. We use a mathematical model where the columns can be easily and naturally interpreted as truck routes. We solve this model using column generation. As a first step, we relax the integrality of the decision variables and consider only a subset of feasible routes. The feasible routes with a potential to improve the solution are added iteratively to the model. A time-space network is used both to represent the impacts of unforeseen events and to generate these routes. The solution obtained is generally fractional and a heuristic branch-and-price algorithm is used to find integer solutions. Several disruption scenarios were developed to test the proposed approach on case studies from the Canadian forest industry and numerical results are presented for the three contexts