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

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

Simulation and optimization methods for logistics pooling in the outbound supply chain

Logistics pooling and collaborative transportation systems are relatively new concepts in logistics research, but are very popular in practice. This communication proposes a conceptual framework for logistics and transportation pooling systems, as well as a simulation method for strategic planning optimization. This method is based on a twostep constructive heuristic in order to estimate for big instances the transportation and storage costs at a macroscopic level. Four possible scenarios are explored and commented. Finally, a socio-economic analysis based on 20 semi-directive interviews is presented to propose the limitations and obstacles of logistics poolingLogistics pooling, supply chain management, optimization, group reasoning, simulation

A Supporting Decision Tool for the Integrated Planning of a Logistic Network

none4Design, management and control of a logistic distribution system are very critical issues in supply chain management. They involve a large number of interdependent decisions, such as the determination of the best location and capacity of a distribution center (DC), a production plant, a wholesaler etc., the allocation of customer demand to suppliers, e.g. regional DC (RDC), the adoption of a transportation mode, e.g. rail and truck, the vehicles routing adopting/not adopting a groupage strategy. This chapter presents an original and automatic supporting decisions platform for the integration of strategic (long-term), tactical (mid-term) and operational (short-term) decisions in the design, management and control of a logistic network including up to four operating levels: sources (production plants), central distribution centers (CDCs), RDCs, and customers. A case study is illustrated and obtained results discussed in presence of different problem settings and operating hypotheses.openMANZINI R.; BORTOLINI M.; GAMBERI M.; MONTECCHI M.MANZINI R.; BORTOLINI M.; GAMBERI M.; MONTECCHI M

An optimization and simulation framework for integrated tactical planning of wood harvesting operations and lumber production

La planification tactique des opérations forêt-usines est centrée sur trois éléments principaux : la récolte, le transport et la transformation du bois. La planification de cette chaine d’approvisionnement est très complexe. Il existe déjà des outils pour faciliter la décision de décideur tels que FPInterface et Optitek, tous deux développés par FPInnovations. Cette mémoire vise à développer un module d’optimisation qui est connecté aux utiles de simulation. LogiOpt est constituée d'un modèle mathématique. Le modèle développé vise l’optimisation de la chaîne d’approvisionnement entre la forêt et l’usine en concentrant les efforts sur les activités que l’entreprise planifie conjointement avec son entrepreneur d’opérations forestières principal. Grâce à ces solutions de logiciels de simulation et de notre modèle mathématique, nous combinons à la fois dans notre cadre récolte, le transport, l'allocation des bois et des opérations de production. Pour tester notre model mathématique, nous avons utilisé les données d’une année d’exploitation à une entreprise québécoise œuvrant dans le milieu forestier. Nous avons comparé nos résultats avec un plan tactique manuel « simulé ». De ce fait, nous avons constaté que LogiOpt effectue une meilleure allocation de la matière première en allant récolter dans moins de blocs de récolte tout en utilisant des bois ayant un meilleur rendement en usine. Conséquemment, on produit plus de produits finis en usine tout en utilisant la même quantité de bois qu’un plan tactique plus traditionnel.Forest and sawmills tactical planning is based on three main elements: wood harvesting, wood transportation and wood transformation. Planning the whole supply chain, is quite complex. Tools have been built to help manager in his decision process, for example FPInterface and Optitek, which were developed by FPInnovations. The aim of this thesis is to develop an optimization module, LogiOpt, which will be integrated to simulation tools. LogiOpt is made of a mathematical model. The developed model aims at optimizing the supply chain between the forest and the mills. Using simulation software solutions and our mathematical model, we combine at the same time in our framework harvesting, transportation, wood allocation and production operations. To test our mathematical model, we used data obtained from one business year of a Quebec based wood manufacturer. We compared our results with a manual simulated tactical plan. In this regard, we observed that LogiOpt performs better in wood allocation between sawmills, harvesting in less harvesting while using wood with better output. We then end up producing more finished products at sawmills using the same wood quantity as a traditional tactical plan

Integrated strategic and tactical optimization of animal-waste sourced biopower supply chains

International audience—Many models have been recently developed for the optimization of biomass related supply chains. However, models for biopower supply chains powered by animal waste have not received much attention yet. In this paper, we propose a mixed integer linear programming model for supplier selection and procurement planning for a biopower plant. The model integrates time window constraints for the collection of animal waste as well as inventory constraints. We show that the model is intractable with a state-of-the art commercial solver and propose a heuristic approach based on the Adaptive Large Neighbourhood Search (ALNS) framework. We show the efficiency of this approach on a case study in central France

Service supply chain management : a hierarchical decision modeling approach

A Service Supply Chain (SSC) may be described as a network of service provider facilities (in-house or outsourced), each of which is able to process one or more service tasks on an as needed basis. Two key characteristics of a SSC are (i) the business service is decomposable into several sequential tasks that can be processed by different service providers, and (ii) the primary capacity resource is skilled labor. SSCs are increasingly being developed by companies that experience a high variability of demand for their services (e.g., loan processing, analytical consulting services, emergency repair crews, claims processing, etc.). Typically, the customer wait time penalty is very high, to the extent that if the service is not provided within a certain time, the customer service request will abort. As a result, the service provider needs to maintain sufficient processing capacity to meet peak levels of demand. The primary advantage of a SSC, relative to a traditional dedicated facility, is that the processing capacity (labor) can be economically adjusted (lower hiring and firing costs) to match changes in the current demand level. In this dissertation, a hierarchical framework for modeling the decision structure in SSCs is developed. This framework introduces and defines the key SSC entities: service products, service jobs, service providers, and the parameters for characterizing the demand behavior. As part of the framework two problems are formulated and solved. First, given that Service Supply Chains are intended to be dynamic delivery networks that efficiently respond to demand variations, a strategic problem is which candidate service providers are selected to form the SSC network, and how the service tasks are assigned within the provider network. The problem is formulated and solved as a binary program. Second, a consequent tactical problem is how the workforce level at each service provider is dynamically adjusted (hiring and firing) as the real time demand data comes in the problem is formulated and solved as a linear program that bounds a mixed integer program (MIP). The strategic model takes the demand parameters, the competing providers’ information, and the service and tasks parameters, to select the providers that are going to become part of the SSC and assign tasks to them. A method to quantify cumulative demand variation per seasonal cycle is presented to derive aggregate demand parameters from the forecast. The design objective of the strategic model is to minimize set up cost and projected operational cost. The objective is achieved by simultaneously minimizing capital cost, hiring cost, firing cost, service delay cost, excess capacity cost, labor cost, and quality cost while fulfilling the capacity, tasks assignment, facility installation, and task capability constraints. The tactical model is constrained by the providers and task assignment resulting from the strategic model. It uses a more accurate demand forecast, and minimizes actual operational costs represented by hiring cost, firing cost, backlog cost and labor cost, while fulfilling the production balance, routing, capacity, workforce balance and demand constraints. It is solved in two phases. A relaxed model is solved as an LP and its solution is used for bounding a MIP problem. Finally, the behavior of the two models is studied by performing numerical experiments changing key supply chain parameters such as hiring and firing cost, demand variability, labor cost, and backlog cost

Network design decisions in supply chain planning

Structuring global supply chain networks is a complex decision-making process. The typical inputs to such a process consist of a set of customer zones to serve, a set of products to be manufactured and distributed, demand projections for the different customer zones, and information about future conditions, costs (e.g. for production and transportation) and resources (e.g. capacities, available raw materials). Given the above inputs, companies have to decide where to locate new service facilities (e.g. plants, warehouses), how to allocate procurement and production activities to the variousmanufacturing facilities, and how to manage the transportation of products through the supply chain network in order to satisfy customer demands. We propose a mathematical modelling framework capturing many practical aspects of network design problems simultaneously. For problems of reasonable size we report on computational experience with standard mathematical programming software. The discussion is extended with other decisions required by many real-life applications in strategic supply chain planning. In particular, the multi-period nature of some decisions is addressed by a more comprehensivemodel, which is solved by a specially tailored heuristic approach. The numerical results suggest that the solution procedure can identify high quality solutions within reasonable computational time

Models, methods and algorithms for supply chain planning

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.An outline of supply chains and differences in the problem types is given. The motivation for a generic framework is discussed and explored. A conceptual model is presented along with it application to real world situations; and from this a database model is developed. A MIP and CP implementations are presented; along with alternative formulation which can be use to solve the problems. A local search solution algorithm is presented and shown to have significant benefits. Problem instances are presented which are used to validate the generic models, including a large manufacture and distribution problem. This larger problem instance is not only used to explore the implementation of the models presented, but also to explore the practically of the use of alternative formulation and solving techniques within the generic framework and the effectiveness of such methods including the neighbourhood search solving method. A stochastic dimension to the generic framework is explored, and solution techniques for this extension are explored, demonstrating the use of solution analysis to allow problem simplification and better solutions to be found. Finally the local search algorithm is applied to the larger models that arise from inclusion of scenarios, and the methods is demonstrated to be powerful for finding solutions for these large model that were insoluble using the MIP on the same hardware