University of Technology of Troyes




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Ph.D defense William Javier Guerrero Rueda

Model and optimization methods for LRP with inventory constraints

  The problem of designing a supply chain including simultaneously routing and inventory management decisions is studied in this thesis. The objective is to select a subset of depots to open, the inventory policies for a 2-echelon system, and the set of routes to perform distribution from the upper echelon to the next using a homogeneous fleet of vehicles over a finite planning horizon. Demand is considered to be known. Applications are found in humanitarian logistics, military logistics, and supply chain design on the pharmaceutical industry, among others.

    To solve the problem, two matheuristic procedures are developed. On the first part a cooperative algorithm combining exact methods for the supply chain design problem and routing heuristics is presented. On the second part, a partition is proposed using a Dantzig-Wolf reformulation on the routing variables. An hybridization between column generation, Lagrangian relaxation and local search is proposed in this part, put together as a heuristic method. Furthermore, results demonstrate the capability of the algorithms to compute high quality solutions and empirically estimate the improvement in the cost function of the proposed model when compared to a sequential optimization approach. Furthermore, results of the proposed methodologies on benchmark instances for subproblems are studied as well. Those are the capacitated location-routing problem, the inventory-routing problem, and the generalized elementary shortest path problem.

Advisors : Caroline PRODHON (UTT), Nubia VELASCO (Univ. Los Andes)

 Date : 27/01/2014

wi-guerr @

Ph.D defense Cadet David Joseph

Flow optimization : application to the animal nutrition distribution problems

This research concerns solving the Multi-Compartment Vehicle Routing Problem (MC-VRP) in the context of animal nutrition industry. Research and application work focuses on distribution in food industry.

Despite its vast application in industry, little attention has been paid to the MC-VRP. We address three classes of MC-VRP in this research. Firstly, we propose two metaheuristics, "Greedy Randomized Adaptive Search Procedure" (GRASP) and "Iterated Local Search procedure" (ILS), in order to solve a MC-VRP with a fixed-sized compartment dedicated to each product. Also, an extension of this problem to variable-sized compartments which we call Flexible Compartments Vehicle Routing Problem (FC-VRP) is studied. Further, we propose a GRASP and a Multi Start ILS to solve a MC-VRP problem with assignment decisions of each compartment to one client and one product.

Finally, some application work is presented. Experiments intended to measure performance in the context of food distribution to cattle were conducted for Nestal company. Decision support tools had been developed and implemented for this company.

Advisors: Christian PRINS, Farouk YALAOUI

Date : 18 / 12 / 2013

Cadet David JOSEPH
cadet_david.joseph @

Ph.D defense Yassine Ouazene

Mathematical modeling, analysis and optimization of production lines design

During the design phase of a production system, all functional and technological alternatives should be explored in order to propose the best possible solutions. This often results in a combination of several sub-problems such as: selection of pieces of equipments from a set of candidate solutions for each manufacturing operation, dimensioning and allocation of buffers and storage areas, balancing workload among the different workstations, the specification of the type and capacity of the material handling system and the layout of equipments which consists of determining which workstations should be adjacent to each other and how they should be connected. In this context, we were interested in performance evaluation and optimization of serial production lines which are very common in high volume production systems. We have proposed a new analytical method, known as « Equivalent Machines Method» to evaluate the production line throughput. This method has the advantages to be more accurate and faster than the existing approaches in the literature. We have also established the relevance of this method for evaluating the production rate of series-parallel systems and other serial lines with machines having multiple failure modes. We have also developed a new algorithm based on nonlinear programming approach to solve the buffer allocation problem.

Advisors : Alice YALAOUI, Hichem CHEHADE

Date : 29 / 11 /2013

Ph.D defense Julien Michallet

Periodic vehicle routing problem with security constraints or quality of service requirements

This thesis is dedicated to the periodic vehicle routing problem when applied to the transportation of valuable goods. Specifics constraints have to be defined to ensure the security of the convoy.  The periodic vehicle routing problem with time spread constraints on services (PVRPTS) is defined and a mathematical model is given. The goal is to serve a set of customers over several days such that their visit times differ by a minimum amount. The depicted model is discussed and two constructive heuristics are designed and assessed.  A Multi-start iterated local search (MS-ILS) is proposed to solve this problem. The results shows that the method outperform the two previous heuristics. For the sake of comparison with previous approach, the MS-ILS evaluated on a more classical problem : the vehicle routing problem with soft time windows (VRPSTW). The method proves very competitive, producing new best known solutions.  The MS-ILS is then adapted to solve the consistent vehicle routing problem (ConVRP). Unlike the PVRPTS, the goal of the ConVRP is to deliver customers with intermittent demand with regularity in terms of service times and drivers. The method demonstrate his flexibility and produce good results.   Finally, the development performed at Nexxtep Technologies are depicted. They encompass commercial-software design and implementation of the the proposed methods.

Advisors : Lionel AMODEO, Christian PRINS

Date : 15 / 11 / 2013

julien.michallet @