원문정보
초록
영어
Heuristic evolutionary optimization algorithms are the solutions to many engineering optimization problems. Differential evolution (DE) is a real stochastic evolutionary parameter optimization in current use.DE does not require more control parameters compared to other evolutionary algorithms. Master Production Scheduling (MPS) is posed as one of multi objective parameter optimization problems and often require an optimal solution for the success of a business organization by balancing demand and supply. This work reviews some of the fundamental theory of differential evolution, the methodology for master production scheduling calculation and most important results. The results available for the existing algorithms are compared with results obtained by the proposed evolutionary algorithm. The analysis reveals that the DE algorithm provides a better solution with reasonable computational time.
목차
1. Introduction
2. Multi-objective optimization for MPS using differential evolution (MOMDE)
2.1. Chromosome representation
2.2. Basics of differential evolution
2.3. Initial population criteria
2.4. The stopping criteria
3. The Fitness Function
4. MPS problem considered
5. Results and discussion
6. Conclusions and Future Scope
References