Parallel reactive tabu search for job-shop scheduling problems considering energy management
Authors:
- 1 November 2017
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-8
Abstract
This paper presents parallel reactive tabu search for job-shop scheduling problems considering energy management. Production scheduling of factories should be minimized to keep customer delivery time. Since reduction of energy costs is important, operational planning of energy plants in factories should be optimized as well. However, the scheduling in factories and optimization of energy plants have been solved separately so far. Although energy costs have been ignored when the scheduling is optimized, it should be considered from the management point of view. This paper tries to optimize production scheduling and operational planning of energy plant simultaneously to minimize maximum end time of all factory operations (makespan) and total energy costs using parallel reactive tabu search.Keywords
This publication has 16 references indexed in Scilit:
- Dependable Parallel Differential Evolutionary Particle Swarm Optimization for On-line Optimal Operational Planning of Energy PlantsIEEJ Transactions on Electronics, Information and Systems, 2017
- Reactive Tabu Search for Job-shop scheduling problems considering peak shift of electric power energy consumption2016
- A Bee Colony Optimization Algorithm to Job Shop Scheduling2006
- A new approach to job shop scheduling problems with due date constraints considering operation subcontractsInternational Journal of Production Economics, 2005
- A parallel Tabu search algorithm for the 0-1 multidimensional knapsack problem2002
- Tabu Search1997
- Evolutionary Search and the Job Shop1996
- The Reactive Tabu SearchINFORMS Journal on Computing, 1994
- Applying tabu search to the job-shop scheduling problemAnnals of Operations Research, 1993
- Algorithms for Solving Production-Scheduling ProblemsOperations Research, 1960