Nathalie Bostel

A facility location model for logistics systems including reverse flows: The case of remanufacturing activities

Abstract After a brief introduction to the basic concepts of reverse logistics, we present a two-level location problem with three types of facility to be located in a specific reverse logistics system, named a Remanufacturing Network (RMN). For this problem, we propose a 0–1 mixed integer programming model, in which we simultaneously consider “forward” and “reverse” flows and their mutual interactions. An algorithm based on Lagrangian heuristics is developed and the model is tested on data adapted from classical test problems.

A tabu search algorithm for the integrated scheduling problem of container handling systems in a maritime terminal

The scheduling problem in a container terminal is characterized by the coordination of different types of equipment. In this paper, we present an integrated model to schedule the equipment. The objective is to minimize the makespan, or the time it takes to serve a given set of ships. The problem is formulated as a Hybrid Flow Shop Scheduling problem with precedence and Blocking constraints (HFSS-B). A tabu search algorithm is proposed to solve this problem. Certain mechanisms are developed and introduced into the algorithm to assure its quality and efficiency. The performance of the tabu search algorithm is analyzed from the computational point of view.

Models and Algorithms for Container Allocation Problems on Trains in a Rapid Transshipment Shunting Yard

Multimodal transport of containers can be an alternative to the road transportation but it requires to be competitive in terms of quality of service and price. In rail rail container terminals, new techniques are developed to facilitate rapid transfers of the containers between trains. In this article, we address the problem of the optimization of the operations management of rapid rail rail transshipment shunting yards. We are interested specifically in the optimization of containers allocation on tra ins (for the initial loading and their reloading after transshipment). We have developed a class of models with different levels of complexity and realism and we have proposed optimal and heuristic methods to solve them. The experimental results on realistic datasets are very promising in terms of the minimization of the container moves in a terminal as well as the use and sizing of the handling equipments.

The Design, Planning, and Optimization of Reverse Logistics Networks

Reverse logistics is concerned with the return flows of products or equipment back from the consumer to the logistics network for reuse, recovery or recycling for environmental, economic or customer service reasons. In this paper, we review applications, case studies, models and techniques proposed for the design, planning and optimization of reverse logistics systems. We consider both cases of separate and integrated handling of original products and return flows throughout the logistics network. According to the hierarchical planning framework for logistics systems, the works are described in relation to their contribution to strategic, tactical or operational planning. Major contributions concern facility location, inventory management, transportation and production planning models. Directions for further research are indicated in all of these areas as well as for the general development of reverse logistics activities in a supply chain network.

Multiperiod Planning and Routing on a Rolling Horizon for Field Force Optimization Logistics

We address the problem of the planning and routing of technician visits to customers in the field, for maintenance or service logistics activities undertaken by utilities. The plans must be designed over a multiperiod, rolling horizon and updated daily. We have developed a memetic algorithm and a column generation/branch and bound heuristic in order to optimize an initial plan over a static horizon. We have then adapted our procedures to cope with a rolling horizon context, when a new plan has to be determined after the execution of each first daily period of the previous plan. We have tested our procedures on realistic data from the water distribution sector, and obtained good solutions in a reasonable amount of time. We show in particular the advantage of reutilization of partial solutions from the previous plan for the optimization of each new plan. Directions for further research are then indicated.

An exact algorithm and a metaheuristic for the multi-vehicle covering tour problem with a constraint on the number of vertices

The multi-vehicle covering tour problem (m-CTP) involves finding a minimum-length set of vehicle routes passing through a subset of vertices, subject to constraints on the length of each route and the number of vertices that it contains, such that each vertex not included in any route lies within a given distance of a route. This paper tackles a particular case of m-CTP where only the restriction on the number of vertices is considered, i.e., the constraint on the length is relaxed. The problem is solved by a branch-and-cut algorithm and a metaheuristic. To develop the branch-and-cut algorithm, we use a new integer programming formulation based on a two-commodity flow model. The metaheuristic is based on the evolutionary local search (ELS) method proposed in [23]. Computational results are reported for a set of test problems derived from the TSPLIB.

An exact algorithm and a metaheuristic for the generalized vehicle routing problem with flexible fleet size

The generalized vehicle routing problem (GVRP) involves finding a minimum-length set of vehicle routes passing through a set of clusters, where each cluster contains a number of vertices, such that the tour includes exactly one vertex from each cluster and satisfies capacity constraints. We consider a version of the GVRP where the number of vehicles is a decision variable. This paper introduces a new mathematical formulation based on a two-commodity flow model. We solve the problem using a branch-and-cut algorithm and a metaheuristic that is a hybrid of the greedy randomized adaptive search procedure (GRASP) and the evolutionary local search (ELS) proposed in [18]. We perform computational experiments on instances from the literature to demonstrate the performance of our algorithms.

Solving the close-enough arc routing problem

The close-enough arc routing problem has an interesting real-life application to routing for meter reading. In this article, we propose a new mathematical formulation for this problem. We analyze our formulation and compare it with two formulations in the literature. We also develop branch-and-cut algorithms to solve the problem to optimality. We present computational results for instances based on three types of graphs: directed, undirected, and mixed. Copyright

An integrated approach for modeling and solving the scheduling problem of container handling systems

An integrated model is presented to schedule the container handling system. The objective is to improve the cooperation between different types of equipments, and to increase the productivity of the terminal. The problem is formulated as a Hybrid Flow Shop Scheduling problem with precedence constraint, setup times and blocking (HFSS-B). A tabu search algorithm is proposed to solve this problem. The quality and efficiency of the proposed algorithm is analyzed from the computational point of view.

Exact and hybrid methods for the multiperiod field service routing problem

This article deals with a particular class of routing problem, consisting of the planning and routing of technicians in the field. This problem has been identified as a multiperiod, multidepot uncapacitated vehicle routing problem with specific constraints that we call the multiperiod field service routing problem (MPFSRP). We propose a set covering formulation of the problem for the column generation technique and we develop an exact branch and price solution method for small-sized instances. We also propose several heuristic versions for larger instances. We present the results of experiments on realistic data adapted from an industrial application.