In this thesis, we review and synthesize a number of algorithmic approaches for optimizing the job-shop scheduling problem (JSSP). The complexity of the JSSP leads to large and difficult combinatorial optimization models. In Chapter 1, we review first an analytical method based on Mixed Integer Programming (MIP). Second, we review an assumption-based heuristic method. In Chapter 2, the JSSP is ...

We present a cooperation technique using an accurate management of nogoods to solve a hard real-time problem which consists in assigning periodic tasks to processors in the context of fixed priorities preemptive scheduling. The problem is to be solved off-line and our solving strategy is related to the logic based Benders decomposition. A master problem is solved using constraint programming wh...

The problem addressed in this paper is related to an aerospace company seeking to change its outsourcing strategies in order to meet the expected demand increase and customer satisfaction requirements regarding delivery dates and amounts. A bilinear goal programming model is developed to achieve the company’s objectives. A modified Benders decomposition method is successfully applied to handle ...

Over the years, various techniques have been proposed to speed up the classical Benders decomposition algorithm. The work presented in the literature has focused mainly on either reducing the number of iterations of the algorithm or on restricting the solution space of the decomposed problems. In this article, a new strategy for Benders algorithm is proposed and applied to two case studies in o...

Bilevel optimization formulates hierarchical decision-making processes that arise in many real-world applications, such as pricing, network design, and infrastructure defense planning. In this paper, we consider a class of bilevel problems which the upper level problem features some integer variables lower enjoys strong duality. We propose dedicated Benders decomposition method for solving prob...

This paper introduces a formulation and a solution methodology for the problem of optimizing the supply chain (or logistics network) of a manufacturing firm. The problem is modeled as a linear mixed-integer program with binary variables associated with design decisions such as location, product range assignment and transportation mode selection, and continuous variables representing the flows o...

We apply logic-based Benders decomposition (LBBD) to two-stage stochastic planning and scheduling problems in which the second stage is a task. solve master problem with mixed integer/linear programming subproblem constraint programming. As cuts, we use simple no-good cuts as well analytic develop for this application. find that LBBD computationally superior integer L-shaped method. In particul...