From packing to dispatching: supply chain optimization techniques

This thesis aims at proposing relevant optimization techniques, such as metaheuristics, for various logistics problems faced by international companies. Four different projects are studied, each one having its own specificity. They all appear at different levels of the supply chain

A push shipping-dispatching approach for high-value items: from modeling to managerial insights, proceedings of the international conference optimization and decision science

real shipping-dispatching problem is considered in a three-level supply chain (plant, wholesalers, shops). Along the way, different perturbations are expected (when manufacturing, when forecasting the demand, and when dispatching the inventory from the wholesalers level), and accurate reactions must be taken. An integer linear program is proposed and some managerial insights are given

Metaheuristics for truck loading in the car production industry

The delivery of goods to car factories is a challenging problem. The French car manufacturer Renault is facing daily a complex truck loading problem where various goods must be packed into a truck such that they fulfill different constraints. As trucks can deliver goods to different factories on the same tour, classes of items have been defined, where a class is associated with a delivery point. The consideration of these classes in addition to large standard deviations over the sizes of the items are new features in the packing literature. Because of the problem structure and of the computation time limit constraint imposed by practitioners, it will be shown that exact algorithms are not appropriate from a practical standpoint. We propose efficient metaheuristics to tackle this problem. First, in contrast with the classical literature, the proposed tabu search relies on the joint use of different types of moves (an efficient diversification mechanism is also proposed to enhance its performance). Then, the recombination operator used in the developed genetic algorithm takes into account all the problem features and is able to build well-balanced offspring solutions. Finally, within the framework of ant algorithms, the benefit of an unconventional decision selection mechanism is discussed. An extension of the problem is proposed at the end, which consists in tackling all the instances within a common time limit. In this context, it will be showed that a combination of the algorithms is the most powerful strategy

Online vehicle routing and scheduling with continuous vehicle tracking

Abstract This paper proposes an extension to an online vehicle routing problem described i

Inventory deployment with uncertainty on production and lead-times, proceedings of the international conference on industrial engineering and systems management

An international Swiss company is facing a complex inventory-deployment problem where expensive items of different models must be dispatched to wholesalers to finally reach the shops. Perturbations are expected at two levels (namely, production and transportation), and efficient reactions must be implemented to face to these uncertainties. Fast and efficient solution methods are proposed to solve realistic instances

Heuristics for a multi-machine multi-objective job scheduling problem with smoothing costs Proceeding for the GOL 2012 conference General Terms Metaheuristics, job scheduling, multi-resource

ABSTRACT We propose a new multi-objective job scheduling problem on non-identical machines involving job and machine dependent setup costs and times, as well as smoothing costs. Smoothing issues are very important in several settings, such as for example car production, since they allow to balance resource utilization over an assembly line. In this paper, we describe the problem, give a mixed integer linear programming formulation, and propose several heuristics: three greedy procedures, two descent approaches, and a tabu search. Experiments, performed on realistic and challenging instances with up to 500 jobs and 8 machines, show that tabu search is a powerful method: it gives the best results for the large instances and is very competitive on the small instances

Impact of vehicle tracking on a routing problem with dynamic travel times

This paper evaluates the benefits of data obtained via modern information technologies, such as global positioning systems, when solving a vehicle routing problem with dynamic customer requests and dynamic travel times. It is empirically demonstrated that substantial improvements are achieved over a previously reported model which does not assume the availability of such information. We also analyze how the system handles dynamic perturbations to the travel times that lead to earliness or lateness in the planned schedule