Adjunct Professor - Department of Accounting Auditing and Business Analytics
Senoussi, Ahmed; Dauzère-Pérès, Stéphane, Brahimi, Nadjib, Penz, Bernard & Mouss, Nadia Kinza (2018)
Heuristics Based on Genetic Algorithms for the Capacitated Multi Vehicle Production Distribution Problem
Computers & Operations Research, 96, s. 108- 119. Doi: 10.1016/j.cor.2018.04.010
In this paper, we consider the integration of production, inventory and distribution decisions in a sup- ply chain composed of one production facility supplying several retailers located in the same region. The supplier is far from the retailers compared to the distance between retailers. Thus, the traveling cost of each vehicle from the supplier to the region is assumed to be fixed and there is a fixed delivery (service) cost for each visited retailer. The objective is to minimize the sum of the costs at the production facility and at the retailers. The problem is more general than the One-Warehouse Multi-Retailer problem and is a special case of the Production Routing Problem. Five heuristics based on a Genetic Algorithm are proposed to solve the problem. In particular, three of them include the resolution of a Mixed Integer Pro- gram as subproblem to generate new individuals in the population. The results show that the heuristics can find optimal solutions for small and medium size instances. On large instances, the gaps obtained by the heuristics in less than 300 s are better than the ones obtained by a standard solver in two hours.
Kao, Yu-Ting; Dauzère-Pérès, Stéphane, Blue, Jakey & Chang, Shi-Chung (2018)
Impact of integrating equipment health in production scheduling for semiconductor fabrication
Computers & industrial engineering, 120, s. 450- 459. Doi: 10.1016/j.cie.2018.04.053
Monitoring the Equipment Health Indicator (EHI) of critical machines helps effectively to maintain process quality and reduce wafer scrap, rework, and machine breakdowns. To model and illustrate the integration of EHI in scheduling decisions to balance between productivity and quality risk, this paper presents two mixed integer linear programs to schedule jobs on heterogeneous parallel batching machines. The capability of a machine to process a job is categorized as preferred, acceptable, and unfavorable based on the job requirements. The quality risk of processing a job by a machine is a function of its EHI and the capability level of the machine for the job, which is modeled as a penalty in the objective function of trading-off between productivity and quality risk. The first model is static and assumes constant EHI of machines on the scheduling horizon, whereas the second model considers the EHI dynamics, i.e., the machine condition deteriorates over time based on the scheduled jobs. Numerical experiments indicate the potential applications of using EHI-integrated scheduling approaches to analyze and optimize the trade-off between productivity and quality risk.
Absi, Nabil; Archetti, Claudia, Dauzère-Pérès, Stéphane, Feillet, Dominique & Speranza, M. Grazia (2018)
Comparing sequential and integrated approaches for the production routing problem
European Journal of Operational Research, 269, s. 633- 646. Doi: 10.1016/j.ejor.2018.01.052
We consider the Production Routing Problem where production planning, inventory management and distribution planning decisions must be taken. We compare two sequential approaches, one in which production decisions are optimized first and one in which distribution decisions are optimized first, with an integrated approach where all decisions are simultaneously optimized. Some properties of the solutions obtained with the different approaches are shown. Computational experiments are performed on instances of different size which are generated using two critical parameters. The numerical results illustrate the properties and show that the benefits of the integrated approach over the two sequential ones depend on the trade-off between production and distribution costs and on the trade-off between setup and inventory costs in production.
Rowshannahad, Mehdi; Absi, Nabil, Dauzère-Pérès, Stéphane & Cassini, Bernard (2018)
Multi-item bi-level supply chain planning with multiple remanufacturing of reusable by-products
International Journal of Production Economics, 198, s. 25- 37. Doi: 10.1016/j.ijpe.2018.01.014
In this paper, we investigate a multi-item production planning problem in which remanufacturable raw materials are used for manufacturing the final products. The used raw material (considered as a kind of by-product) needs to be remanufactured before being suitable to be used again to manufacture other final products. However, byproducts can be remanufactured only a given number of times. The manufacturing and remanufacturing processes are performed in separated production processes with limited capacity. Each product may be produced using specific raw material references (newly purchased and/or remanufactured). The original industrial case study is based on the supply chain of Silicon-On-Insulator fabrication units. The problem is modeled as a mixed integer linear mathematical program. Using numerical examples based on industrial data, the model is validated and its behavior is analyzed. Finally, some industrial and academic perspectives to this study are proposed.
Shen, Liji; Dauzère-Pérès, Stéphane & Neufeld, Janis S. (2017)
Solving the flexible job shop scheduling problem with sequence-dependent setup times
European Journal of Operational Research, 265(2), s. 503- 516. Doi: 10.1016/j.ejor.2017.08.021
This paper addresses the flexible job shop scheduling problem with sequence-dependent setup times and where the objective is to minimize the makespan. We first present a mathematical model which can solve small instances to optimality, and also serves as a problem representation. After studying structural properties of the problem using a disjunctive graph model, we develop a tabu search algorithm with specific neighborhood functions and a diversification structure. Extensive experiments are conducted on benchmark instances. Test results first show that our algorithm outperforms most existing approaches for the classical flexible job shop scheduling problem. Additional experiments also confirm the significant improvement achieved by integrating the propositions introduced in this study.
Brahimi, Nadjib; Absi, Nabil, Dauzère-Pérès, Stéphane & Nordli, Atle (2017)
Single-item dynamic lot-sizing problems: An updated survey
European Journal of Operational Research, 263(3), s. 838- 863. Doi: 10.1016/j.ejor.2017.05.008
Knopp, Sebastian; Dauzère-Pérès, Stéphane & Yugma, Claude (2017)
A batch-oblivious approach for Complex Job-Shop scheduling problems
European Journal of Operational Research, 263(1), s. 50- 61. Doi: 10.1016/j.ejor.2017.04.050
Altazin, Estelle; Dauzère-Pérès, Stéphane, Ramond, François & Trefond, Sabine (2017)
Rescheduling through stop-skipping in dense railway systems
Transportation Research Part C: Emerging Technologies, 79, s. 73- 84. Doi: 10.1016/j.trc.2017.03.012
Dauzère-Pérès, Stéphane; Hassoun, Michael & Sendon, Alejandro (2016)
Allocating metrology capacity to multiple heterogeneous machines
International Journal of Production Research, 54(20), s. 6082- 6091. Doi: 10.1080/00207543.2016.1187775
Dauzère-Pérès, Stéphane (2017)
Achievements and Lessons Learned from a Long-Term Academic-Industrial Collaboration
[Academic lecture]. 2017 Winter Simulation Conference.
I had the opportunity to work for about 14 years on many different projects with two manufacturing sites of the French-Italian semiconductor company STMicroelectronics. Supported by European, national and industrial projects, this still active long-term academic-industrial collaboration led to many scientific and industrial achievements, spreading to other companies. Through regular exchanges, engineers, researchers, PhD and Master students were able to present their problems, their advances and generate new research projects. After some history of the collaboration, the presentation will survey some of the main research and industrial results in qualification and flexibility management, production and capacity planning, scheduling, automated transportation, dynamic sampling and time constraint management. Challenges faced and lessons learned when applying Operations Research and Industrial Engineering in practice, and in particular in semiconductor manufacturing, will be discussed. Benefits for both practitioners and researchers will be emphasized, such as the opportunity to propose and study new relevant problems and develop and apply novel approaches using actual industrial data.
|1992||Paul Sabatier University (Toulouse III), France.||PhD|
|1992||Paul Sabatier University (Toulouse III), France.||PhD|
|2016 - Present||BI Norwegian Business School||Adjunct Professor, Department of Accounting, Auditing and Business Analytics|
|2004 - Present||Ecole des Mines de Saint-Etienne||Professor, Center of Microelectronics in Provence, Georges Charpak Campus|
|2013 - 2014||Ecole des Mines de Saint-Etienne||Director of the Center of Microelectronics in Provence|
|2004 - 2013||Ecole des Mines de Saint-Etienne||Head of the Department of Manufacturing Sciences and Logistics|
|2003 - 2009||Molde University College||Invited Professor|
|2000 - 2004||Ecole des Mines de Nantes||Professor, Department of Automatic Control and Industrial Engineering|