Using multiple objective tabu search and grammars to model and solve multi-objective flexible job shop scheduling problems |
| |
Authors: | Adl Baykaso?lu Lale özbakir Al? ?hsan Sönmez |
| |
Affiliation: | (1) Department of Industrial Engineering, University of Gaziantep, 27310 Gaziantep, Turkey;(2) Department of Industrial Engineering, Erciyes University, Kayseri, Turkey;(3) Department of Management, CAG University, Tarsus—Mersin, Turkey |
| |
Abstract: | A linguistic-based meta-heuristic modeling and solution approach for solving the flexible job shop scheduling problem (FJSSP) is presented in this study. FJSSP is an extension of the classical job-shop scheduling problem. The problem definition is to assign each operation to a machine out of a set of capable machines (the routing problem) and to order the operations on the machines (the sequencing problem), such that predefined performance measures are optimized. In this research, the scope of the problem is widened by taking into account the alternative process plans for each part (process plan selection problem). Probabilistic selection of alternative process plans and machines are also considered. The FJSSP is presented as a grammar and the productions in the grammar are defined as controls (Baykaso lu, 2002). Using these controls and Giffler and Thompson's (1960) priority rule-based heuristic along with the multiple objective tabu search algorithm of Baykaso lu et al. (1999) FJSSP is solved. This novel approach simplifies the modeling process of the FJSSP and enables usage of existing job shop scheduling algorithms for its fast solution. Instead of scheduling job shops with inflexible algorithms that cannot take into account the flexibility which is available in the job shop, the present algorithm is developed which can take into account the flexibility during scheduling. Such an approach will considerably increase the responsiveness of the job shops. |
| |
Keywords: | Scheduling grammars optimization flexibility tabu search |
本文献已被 SpringerLink 等数据库收录! |
|