Stochastic Service Network Design for Intermodal Freight Transportation

In view of the accelerating climate change, greenhouse gas emissions from freight transportation must be significantly reduced over the next decades. Intermodal transportation can make a significant contribution here. During the transportation process, different modes of transportation are combined, enabling a modal shift to environmentally friendly alternatives such as rail and inland waterway transportation. However, at the same time, the organization of several modes is more complex compared to the unimodal case (where, for example, only trucks are employed). In particular, an efficient management of uncertainties, such as fluctuating transportation demand volumes or delays, is required to realize low costs and transportation times, thereby ensuring the attractiveness of intermodal transportation for a further modal shift. Stochastic service network design can explicitly consider such uncertainities in the planning in order to increase the performance of intermodal transportation. Decisions for the network design as well as for the mode choice are defined by mathematical optimization models, which originate from operations research and include relevant uncertainities by stochastic parameters. As central research gap, this dissertation addresses important operational constraints and decision variables of real-life intermodal networks, which have not been considered in these models so far and, in consequence, strongly limit their application in everyday operations. The resulting research contribution are two new variants of stochastic service network design models: The "stochastic service network design with integrated vehicle routing problem" integrates corresponding routing problems for road vehicles into the planning of intermodal networks. This new variant ensures a cost- and delay-minimal mode choice in the case of uncertain transportation times. The "stochastic service network design with short-term schedule modifications" deals with modifications of intermodal transportation schedules in order to adapt them to fluctuating demand as best as possible. For both new model variants, heuristic solution methods are presented which can efficiently solve even large network instances. Extensive case studies with real-world data demonstrate significant savings potentials compared to deterministic models as well as (simplified) stochastic models that already exist in literature

The Two-Echelon Vehicle Routing Problem with Pickups, Deliveries, and Deadlines

This paper introduces the Two-Echelon Vehicle Routing Problem with Pickups, Deliveries, and Deadlines (2E-VRP-PDD), a new and emerging routing variant addressing the operations of logistics companies connecting consumers and suppliers in megacities. Logistics companies typically organize their logistics in such megacities via multiple geographically dispersed two-echelon distribution systems. The 2E-VRP-PDD is the practical problem that needs to be solved within each of such a single two-echelon distribution setting, thereby merging first and last-mile logistics operations. Specifically, it integrates forward flow, reverse flow, and vehicle time-synchronization aspects such as parcel time windows, satellite synchronization, and customer-dependent deadlines on the arrival of parcels at the hub. We solve the 2E-VRP-PDD with a tailored matheuristic that combines a newly developed Adaptive Large Neighborhood Search (ALNS) with a set-partitioning model. We show that our ALNS provides high-quality solutions on established benchmark instances from the literature. On a new benchmark set for the 2E-VRP-PDD, we show that loosening or tightening time restrictions, such as parcel delivery deadlines at the city hub, can lead to an 8.5% cost increase; showcasing the overhead associated with same-day delivery compared to next-day delivery operations. Finally, we showcase the performance of our matheuristic based on real-life instances which we obtained from our industry collaborator in Jakarta, Indonesia. On these instances, which we share publicly and consists of 1500 - 2150 customers, we show that using our ALNS can significantly improve current operations, leading to a 17% reduction in costs

The synchronized multi-commodity multi-service Transshipment-Hub Location Problem with cyclic schedules

The synchronized multi-commodity multi-service Transshipment-Hub Location Problem is a hub location problem variant faced by a logistics service provider operating in the context of synchromodal logistics. The provider must decide where and when to locate transshipment facilities in order to manage many customers’ origin–destination shipments with release and due dates while minimizing a total cost given by location costs, transportation costs, and penalties related to unmet time constraints. The considered synchromodal network involves different transportation modes (e.g., truck, rail, river and sea navigation) to perform long-haul shipments and the freight synchronization at facilities for transshipment operations. To the best of our knowledge, this variant has never been studied before. Considering a time horizon in which both transportation services and demand follow a cyclic pattern, we propose a time–space network representation of the problem and an ad-hoc embedding of the time-dependent parameters into the network topology and the arcs’ weight. This allows to model the flow synchronization required by the problem through a Mixed-Integer Linear Programming formulation with a simplified structure, similar to well-known hub location problems and avoiding complicating constraints for managing the time dimension. Through an extensive experimental campaign conducted over a large set of realistic instances, we present a computational and an economic analysis. In particular, we want to assess the potential benefits of implementing synchromodal logistics operations into long-haul supply-chains managed by large service providers. Since flexibility is one of the main features of synchromodality, we evaluate the impact on decisions and costs of different levels of flexibility regarding terminals’ operations and customers’ requirements

Risk Assessment of Water Transport Enterprises by Modeling Direct and Indirect Threats

Introduction. The methods of traffic modeling by water transport and assessing the risks associated with it is needed to identify the issues of the past period, proposing methods for assessing not only direct but also indirect risks to form the preconditions for preventing them in the postwar reconstruction. The coordination of different transport type’s actions of transport requires an assessment of risks impact of the previous stages of mixed transportation on the formation of the following risks’ stages. Existing methods of assessing such impact need to be improved. Aim and tasks. The aim of this study is creation of methodological approach to risk management in water transport based on a mathematical model for assessing the impact of both direct and indirect risks. The tasks are: to prove that the additive approach of taking risks into account leads to the systematic deviation appearance from the result; take into account the impact on the risk of cargo transportation. Results. It has proved that the calculation of risk as an additive function leads to a systematic deviation from the relevant result. It stated that the risk of each of the next stages of transportation depends on the risks of the previous stages. To increase risk analysis relevance in water transport, the use of an oriented graph in a multidimensional parameter space proposed. It stated that in order to calculate the integrated risk, it is essential building not only the risk matrix but also the risk incidence matrix to take into account their relation to business entities. It established the impact of even minor risks could take the form of a catastrophe, which leads to cargo flows reorientation. It established that: for calculation of integral risk, it is crucial consider direct and indirect influences of risks; risk calculation for water transport also requires risk analysis in related modes of transport. Conclusions. It was established that, when calculating integral risk, it is necessary to consider direct and indirect influences on risks and that the risk calculation for water transport also requires risk analysis in related modes of transport. The proposed approach significantly increases the relevance of water transport risk analysis and allows for managing changes in transportation routes in real time

The one container drayage problem with soft time windows

Intermodal freight transport consists of using different modes of transport without changing the load unit. This results in a significant reduction in the time that goods spend at intermodal terminals, where transshipment takes place. Drayage refers to the transport of freight on trucks among intermodal terminals, depots, customers and suppliers. In spite of the fact that drayage only represents between 5 and 10 percent of total distance, it may amount up to more than 30 percent of the total costs. The aim of this work is to study drayage operations. First, an extensive literature review is undertaken. Since the intermodal transport chain can become more efficient by means of a proper organisation of the drayage movements, the optimization of the daily drayage problem has been identified as one of the main ways of reducing the drayage cost and improving intermodal operations. On this problem, the lack of a common benchmark has hindered reaching further conclusions from all the research carried out. Therefore, this paper proposes a common framework and presents a generalized formulation of the problem, which allows modeling most drayage policies, with the limitation of only considering one-container problems. Results show that flexible tasks in the repositioning of empty containers as well as soft time windows can reduce the operating costs and facilitate the management of drayage companies. This work may help consider adequate policies regarding drayage operations in intermodal terminals

The Mathematical Modeling Stages of Combining the Carriage of Goods for Indefinite, Fuzzy and Stochastic Parameters

Combined cargo transportation in Ukraine is characterized by the presence of uncertain risks. The aim of the article was to propose a mathematical model for choosing the mode of transportation that would correspond to the best value of the integral objective function in the presence of fuzzy, stochastic and uncertain risk parameters. The efficiency of the mathematical model provided the possibility of forming not only long-term forecasts that require significant time, but also short-term forecasts in real time. This allows to quickly change routes and conditions of transportation. Practical testing of the mathematical model revealed the assimilating nature of some uncertain risks. The results of the analysis are given in the article. The realization of such a risk leads to a radical change in all conditions of transportation. Long-term forecasts allow to predict new routes and conditions of transportation

Solution Methods for Service Network Design with Resource Management Consideration

La gestion des ressources, équipements, équipes de travail, et autres, devrait être prise en compte lors de la conception de tout plan réalisable pour le problème de conception de réseaux de services. Cependant, les travaux de recherche portant sur la gestion des ressources et la conception de réseaux de services restent limités. La présente thèse a pour objectif de combler cette lacune en faisant l’examen de problèmes de conception de réseaux de services prenant en compte la gestion des ressources. Pour ce faire, cette thèse se décline en trois études portant sur la conception de réseaux. La première étude considère le problème de capacitated multi-commodity fixed cost network design with design-balance constraints(DBCMND). La structure multi-produits avec capacité sur les arcs du DBCMND, de même que ses contraintes design-balance, font qu’il apparaît comme sous-problème dans de nombreux problèmes reliés à la conception de réseaux de services, d’où l’intérêt d’étudier le DBCMND dans le contexte de cette thèse. Nous proposons une nouvelle approche pour résoudre ce problème combinant la recherche tabou, la recomposition de chemin, et une procédure d’intensification de la recherche dans une région particulière de l’espace de solutions. Dans un premier temps la recherche tabou identifie de bonnes solutions réalisables. Ensuite la recomposition de chemin est utilisée pour augmenter le nombre de solutions réalisables. Les solutions trouvées par ces deux méta-heuristiques permettent d’identifier un sous-ensemble d’arcs qui ont de bonnes chances d’avoir un statut ouvert ou fermé dans une solution optimale. Le statut de ces arcs est alors fixé selon la valeur qui prédomine dans les solutions trouvées préalablement. Enfin, nous utilisons la puissance d’un solveur de programmation mixte en nombres entiers pour intensifier la recherche sur le problème restreint par le statut fixé ouvert/fermé de certains arcs. Les tests montrent que cette approche est capable de trouver de bonnes solutions aux problèmes de grandes tailles dans des temps raisonnables. Cette recherche est publiée dans la revue scientifique Journal of heuristics. La deuxième étude introduit la gestion des ressources au niveau de la conception de réseaux de services en prenant en compte explicitement le nombre fini de véhicules utilisés à chaque terminal pour le transport de produits. Une approche de solution faisant appel au slope-scaling, la génération de colonnes et des heuristiques basées sur une formulation en cycles est ainsi proposée. La génération de colonnes résout une relaxation linéaire du problème de conception de réseaux, générant des colonnes qui sont ensuite utilisées par le slope-scaling. Le slope-scaling résout une approximation linéaire du problème de conception de réseaux, d’où l’utilisation d’une heuristique pour convertir les solutions obtenues par le slope-scaling en solutions réalisables pour le problème original. L’algorithme se termine avec une procédure de perturbation qui améliore les solutions réalisables. Les tests montrent que l’algorithme proposé est capable de trouver de bonnes solutions au problème de conception de réseaux de services avec un nombre fixe des ressources à chaque terminal. Les résultats de cette recherche seront publiés dans la revue scientifique Transportation Science. La troisième étude élargie nos considérations sur la gestion des ressources en prenant en compte l’achat ou la location de nouvelles ressources de même que le repositionnement de ressources existantes. Nous faisons les hypothèses suivantes: une unité de ressource est nécessaire pour faire fonctionner un service, chaque ressource doit retourner à son terminal d’origine, il existe un nombre fixe de ressources à chaque terminal, et la longueur du circuit des ressources est limitée. Nous considérons les alternatives suivantes dans la gestion des ressources: 1) repositionnement de ressources entre les terminaux pour tenir compte des changements de la demande, 2) achat et/ou location de nouvelles ressources et leur distribution à différents terminaux, 3) externalisation de certains services. Nous présentons une formulation intégrée combinant les décisions reliées à la gestion des ressources avec les décisions reliées à la conception des réseaux de services. Nous présentons également une méthode de résolution matheuristique combinant le slope-scaling et la génération de colonnes. Nous discutons des performances de cette méthode de résolution, et nous faisons une analyse de l’impact de différentes décisions de gestion des ressources dans le contexte de la conception de réseaux de services. Cette étude sera présentée au XII International Symposium On Locational Decision, en conjonction avec XXI Meeting of EURO Working Group on Locational Analysis, Naples/Capri (Italy), 2014. En résumé, trois études différentes sont considérées dans la présente thèse. La première porte sur une nouvelle méthode de solution pour le "capacitated multi-commodity fixed cost network design with design-balance constraints". Nous y proposons une matheuristique comprenant la recherche tabou, la recomposition de chemin, et l’optimisation exacte. Dans la deuxième étude, nous présentons un nouveau modèle de conception de réseaux de services prenant en compte un nombre fini de ressources à chaque terminal. Nous y proposons une matheuristique avancée basée sur la formulation en cycles comprenant le slope-scaling, la génération de colonnes, des heuristiques et l’optimisation exacte. Enfin, nous étudions l’allocation des ressources dans la conception de réseaux de services en introduisant des formulations qui modèlent le repositionnement, l’acquisition et la location de ressources, et l’externalisation de certains services. À cet égard, un cadre de solution slope-scaling développé à partir d’une formulation en cycles est proposé. Ce dernier comporte la génération de colonnes et une heuristique. Les méthodes proposées dans ces trois études ont montré leur capacité à trouver de bonnes solutions.Resource management in freight transportation service network design is an important issue that has been studied extensively in recent years. Resources such as vehicles, crews, etc. are factors that can not be ignored when designing a feasible plan for any service network design problem. However, contributions related to resource management issues and service network design are still limited. The goal of the thesis is to fill this gap by taking into account service network design problems with resource management issues. In this thesis, we propose and address three service network design problems that consider resource management. In the first study, we consider the capacitated multi-commodity fixed cost network design with design-balance constraints which is a basic sub-problem for many service design problems because of the capacitated multi-commodity structure as well as its design-balance property. We propose a three-phase matheuristic that combines tabu-search, path-relinking and an exactbased intensification procedure to find high quality solutions. Tabu-search identifies feasible solutions while path-relinking extends the set of feasible solutions. The solutions found by these two meta-heuristics are used to fix arcs as open or close. An exact solver intensifies the search on a restricted problem derived from fixing arcs. The experiments on benchmark instances show that the solution approach finds good solutions to large-scale problems in a reasonable amount of time. The contribution with regard to this study has been accepted in the Journal of Heuristics. In the second study, together with the consideration of the design of routes to transport a set of commodities by vehicles, we extend resources management by explicitly taking account of the number of available vehicles at each terminal. We introduce a matheuristic solution framework based on a cycle-based formulation that includes column generation, slope-scaling, heuristic and exact optimization techniques. As far as we know, this is the first matheuristic procedure developed for a cycle-based formulation. The column generation solves the linear relaxation model and provides a set of cycles to define the approximation model used in slopescaling loop. A heuristic is used to convert each solution to the approximation problem into a feasible solution. Memory-based perturbation procedure is used to enhance the performance of the algorithm. Experiments show that the proposed algorithm is able to find good feasible solutions for the problem. The contribution with regard to this study has been accepted for publication in Transportation Science. In the third study, we examine resources allocation issues in service network design. We aim to address a number of fleet utilization issues which usually appear at the beginning of the season because of the change of demand patterns: 1) reposition resources among terminals to account for shifts in demand patterns; 2) acquire (buy or long-term rent) new resources and as sign them to terminals; 3) outsource particular services. We present an integrated formulation combining these selection-location and scheduled service design decisions. The mixed-integer formulation is defined over a time-space network, the initial period modeling the location de cisions on resource acquisition and positioning, while the decisions on service selection and scheduling, resource assignment and cycling routing, and demand satisfaction being modeled on the rest of the network. We also present a matheuristic solution method combining slope scaling and column generation, discuss its algorithmic performance, and explore the impact of combining the location and design decisions in the context of consolidation carrier service design. This study will be presented at XII International Symposium On Locational Deci sion, in conjunction with the XXI Meeting of EURO Working Group on Locational Analysis, Naples/Capri (Italy), 2014. In summary, three studies are considered in this thesis. The first one considers the capaciated multi-commodity fixed cost network design with design-balance constraints, a basic problem in many service network design problems with design-balance constraints. We propose an ef ficient three-phase matheuristic solution method that includes tabu search, path relinking and exact optimization. In the second study, we propose a new service network design model that takes into account resources limitations at each terminal. We also propose an advanced matheuristic framework solution method based on a cycle-based formulation which includes slope-scaling, column generation, heuristics and exact optimization for this problem. The last study addresses resources allocation issues in service network design. We introduce formula tions that model the reposition, acquisition/renting of resources and outsourcing of services. A solution framework based on the slope-scaling approach on cycle-based formulations is pro posed. Tests indicate that these proposed algorithms are able to find good feasible solutions for each of threse problems

A Bi-Objective Fuzzy Credibilistic Chance-Constrained Programming Approach for the Hazardous Materials Road-Rail Multimodal Routing Problem under Uncertainty and Sustainability

Hazardous materials transportation involves extensive risk and cannot be avoided in practice. An advanced routing, however, can help to reduce the risk by planning the best transportation routes for hazardous materials that can make effective tradeoffs between the risk objective and the economic objective. In this study, we explore the hazardous materials routing problem in the road-rail multimodal transportation network with a hub-and-spoke structure, in which the risk is measured by the multiplication of population exposure and the associated volume of hazardous materials, and minimizing the total risk of all the transportation orders of hazardous materials is set as the risk objective. It is difficult to estimate the population exposure exactly during the routing decision-making process, which results in its uncertainty. In this study, we formulate the uncertain population exposure from a fuzzy programming perspective by using triangular fuzzy numbers. Moreover, the carbon dioxide emission constraint is formulated to realize the sustainable transportation of hazardous materials. To optimize the problem under the above framework, we first establish a bi-objective fuzzy mixed integer nonlinear programming model, and then develop a three-stage exact solution strategy that the combines fuzzy credibilistic chance constraint, linearization technique, and the normalized weighting method. Finally, a computational experiment is carried out to verify the feasibility of the proposed method in dealing with the problem. The experimental results indicate that tradeoffs between the two conflicting objectives can be effectively made by using the Pareto frontier to the hazardous materials routing problem. Furthermore, the credibility level and carbon dioxide emission cap significantly influence the hazardous materials routing optimization. Their effects on the optimization result are quantified by using sensitivity analysis, which can draw some useful insights to help decision makers to better organize the hazardous materials road-rail multimodal transportation under uncertainty and sustainability. Document type: Articl

Developing sustainable supply chains in regional Australia considering demand uncertainty, government subsidies and carbon tax regulation

There is a tremendous opportunity to implement sustainable supply chain management practices in terms of logistics, operations, and transport network in regional Australia. Unfortunately, this opportunity has not been investigated and there is a lack of academic studies in this body of knowledge. This thesis is made up by three related, but independent models designed to efficiently distribute products from a regional hub to other part of the country. This research aims to develop efficient and sustainable supply chain practices to deliver regional Australian products across the country and overseas. As the airports of most Australian capital cities are over-crowded while many regional airports are under-utilised, the first model examines the ways to promote the use of regional airports. Australia is a significant food producer and the agricultural products are primarily produced in regional areas. In the other two models, we focus on the distribution of perishable products from regional Australia. The first model presented in Chapter 2 outlines how different government subsidy schemes can be used to influence airfreight distributions that favour the use of regional airports and promote regional economic development. The model simultaneously considers time-window and release-time constraints as well as the heterogeneous fleet for ground distribution where fuel consumption is subject to load, travel distance, speed and vehicle characteristics. A real-world case study in the state of Queensland, Australia is used to demonstrate the application of the model. The results suggest that the regional airport's advantages can be promoted with suitable subsidy programs and the logistics costs can be reduced by using the regional airport from the industry’s perspective. The second model presented in Chapter 3 examines the impacts of carbon emissions arising from the storage and transportation of perishable products on logistical decisions in the cold supply chain considering carbon tax regulation and uncertain demand. The problem is formulated as a two-stage stochastic programming model where Monte Carlo approach is used to generate scenarios. The aim of the model is to determine optimal replenishment policies and transportation schedules to minimise both operational and emissions costs. A matheuristic algorithm based on the Iterated Local Search (ILS) algorithm and a mixed integer programming is developed to solve the problem in realistic sizes. The proposed model was implemented in a real-world case study in the state of Queensland, Australia to demonstrate the application of the model. The results highlight that a higher emissions price does not always contribute to the efficiency of the cold supply chain system. The third model presented in Chapter 4 investigates the impacts of two different transport modes - road and rail - on the efficiency and sustainability of transport network to deliver meat and livestock from regional Queensland to large cities and seaports. The model is formulated as a mixed-integer linear programming model that considers road traffic congestions, animal welfare, quality of meat products and environmental impacts from fuel consumption of different transport modes. The aim of the model is to determine an optimal network configuration where each leg of journey is conducted by the most reliable, sustainable and efficient transport mode. The results indicate that it would be possible to significantly decrease total cost if a road-rail intermodal network is used. Considering animal welfare, product quality and traffic congestion can have a significant effect on the decisions related to transport mode selection

Book of abstracts of the 24th Euro Working Group on Transportation Meeting

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