240ST Optimization Techniques in Supply Chain

Transcription

1 Coordinating unit: ETSEIB - Barcelona School of Industrial Engineering Teaching unit: OE - Department of Management Academic year: 2017 Degree: ECTS credits: 5 Teaching languages: Spanish Teaching staff Coordinator: Others: Alberto García Villoria Alberto García Villoria Opening hours Timetable: Wednesday: 17:30-19:00 Friday: 17:30-19:00 Prior skills The ones taught in Quantitative Methods in Supply Chain. Degree competences to which the subject contributes Specific: CESCTM1. Designing supply chains, or parts thereof, by applying the methods, techniques and tools that are appropriate for each specific function and purpose. CESC4. Know and apply the techniques of modeling, simulation and optimization to solve the problems involved the design and management of supply chains. Teaching methodology The teaching methodology is divided into three parts: - In-person sessions of lectures. - In-person sessions of practical work (exercises and problems). - Self study, exercises and activities. In the sessions of theoretical content, teachers will introduce the theoretical foundations of the subject, concepts, methods and results, illustrated with suitable examples to facilitate understanding. In the practical sessions, teachers guide the students in applying theoretical concepts to problem solving, basing at all times critical thinking. Exercises will be proposed and students must solve them to promote the use of the basic tools needed to solve the problems. Students must work the contents of the subject and the practical sessions to assimilate concepts. Learning objectives of the subject The main objective is to present a set of techniques to solve combinatorial optimization problems related to the organization and management of production and logistics systems and supply chains, and provide students with a series of tools. It is intended that at the end of the course the student is able to: 1 / 5

2 - modelize management problems in the production and logistics field. - analyze existing procedures for solving these problems. - develop appropriate resolution procedures that provide optimal or feasible solutions. - be capable of efficiently solving various problems of production and logistics systems (production, distribution,...). Study load Total learning time: 125h Hours large group: 30h 24.00% Hours medium group: 15h 12.00% Hours small group: 0h 0.00% Guided activities: 0h 0.00% Self study: 80h 64.00% 2 / 5

3 Content 1. Introduction and basics Learning time: 6h Theory classes: 2h Self study : 4h Combinatorial problems, complexity of a problem and an algorithm, solution and its representation space of solutions, evaluation function, optimality and feasibility, pre-processing, bounds, etc. 2. Exact procedures Learning time: 25h Theory classes: 10h Self study : 15h Dynamic programming, branch and bound 3. Classical heuristic procedures Learning time: 38h Theory classes: 14h Self study : 24h Justification, classification, design, EAGH, concept of neighborhood and local optimum 4. Metaheuristic procedures Learning time: 25h Theory classes: 10h Self study : 15h Metaheuristics of single point (multi-start, GRASP, simulated annealing, tabu search), population metaheuristics (genetic algorithms), calibration of parameters 5. Others non-exact procedures Learning time: 12h Theory classes: 4h Self study : 8h Bounded dynamic programming and branch and bound, mathematical programming based heuristics, matheuristics, hyperheuristics 3 / 5

4 6. Applications Learning time: 20h Theory classes: 6h Self study : 14h Application of some of the studied techniques for solving real cases Qualification system The evaluation is done by various methods: (1) a final exam (EF) consisting of several theoretical and practical exercises in which the student must demonstrate the ability to apply the knowledge learned; (2) a short written practice test (PP), on the same final exam date, about the exercises and problems developed in the practical sessions; (3) teacher evaluation (VP) will be based on participation and level of knowledge demonstrated by students during practical sessions. The final grade for the course, NF, is calculated as follows: NF = 0.8 EF PP max(pp, VP) Regulations for carrying out activities Both the final examination and practice examination, the student can consult all written material. Only the use of calculator is allowed within the electronical devices (can not dispose of mobile phone, laptop or any other tool than the calculator). 4 / 5

5 Bibliography Basic: Gendreau, M.; Potvin, J.-Y. Handbook of metaheuristics [on line]. 2nd ed. New York: Springer, 2010 [Consultation: 05/10/2017]. Available on: < ISBN Hillier, F.S.; Lieberman, G.J. Introducción a la investigación de operaciones. 9a ed. México: McGraw-Hill, ISBN Michalewicz, Z. How to Solve It: Modern Heuristics. 2nd ed. Berlín: Springer, ISBN Talbi, E.G. Metaheuristics: from design to implementation. New Jersey: John Wiley & Sons, ISBN Complementary: Aarts, E. ; Lenstra, J.K. Local Search in Combinatorial Optimization. Princeton: Princeton University Press, ISBN Birattari, M. Tuning metaheuristics. New York: Springer, ISBN García-Villoria, A.; Corominas, A.; Pastor, R. "Pure and hybrid metaheuristics for the response time variability problem". Vasant, Pandian. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance. New York: IGI Global, pp Pinedo, M.L. Planning and Scheduling in Manufacturing and Services [on line]. 2nd ed. New York: Springer, 2009 [Consultation: 01/08/2014]. Available on: < ISBN / 5