A Heuristic Algorithm based on Block Mining and Recombination for Flow Shop Scheduling Problem
碩士 === 元智大學 === 資訊管理學系 === 102 === Genetic algorithm is one kind of heuristic algorithms used to solve permutation flow shop scheduling problem (PFSP). However, the offspring is difficult to have various genes in good solutions because of the evolution of its selection and crossover mechanism and th...
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| Format: | Others |
| Language: | zh-TW |
| Online Access: | http://ndltd.ncl.edu.tw/handle/13905061193357590372 |
| Summary: | 碩士 === 元智大學 === 資訊管理學系 === 102 === Genetic algorithm is one kind of heuristic algorithms used to solve permutation flow shop scheduling problem (PFSP). However, the offspring is difficult to have various genes in good solutions because of the evolution of its selection and crossover mechanism and then leads to local optimum. This study aims to propose a heuristic algorithm based on block mining with recombination (HABMR) for solving PFSP, in which association rule is used to extract various good genes and increase the gene diversity. These genes are also used to generate various block for artificial chromosome combination. The generated blocks can not only improves the opportunities of finding optimal solutions but also enhance the efficiency of convergence.
The proposed HABMR was validated and compared with other five algorithms by numerical experiments, namely Taillard and Reeves in OR-Library. To compare with other algorithms, the solutions of proposed HABMR are closest to the optimal solution. The results showed that HABMR can not only have high the convergence speed but also have better solution quality by increasing the diversity of solutions.
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