文献类型：期刊文献

英文题名：Hybrid Algorithm Based on an Estimation of Distribution Algorithm and Cuckoo Search for the No Idle Permutation Flow Shop Scheduling Problem with the Total Tardiness Criterion Minimization

作者：Sun, Zewen[1];Gu, Xingsheng[1]

机构：[1]East China Univ Sci & Technol, Key Lab Adv Control & Optimizat Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2017

卷号：9

期号：6

外文期刊名：SUSTAINABILITY

收录：;WOS:【SSCI(收录号:WOS:000404133200084)，SCI-EXPANDED(收录号:WOS:000404133200084)】；

基金：This work is supported by the National Natural Science Foundation of China (Grant No. 61573144, 61174040, 61673175) and the Fundamental Research Funds for the Central Universities under Grant 222201717006.

语种：英文

外文关键词：estimation of distribution algorithm (EDA); cuckoo search (CS); HEDA_CS; no idle permutation flow shop scheduling problem (NIPFSP); total tardiness

摘要：The no idle permutation flow shop scheduling problem (NIPFSP) is a popular NP-hard combinatorial optimization problem, which exists in several real world production processes. This study proposes a novel hybrid estimation of the distribution algorithm and cuckoo search (CS) algorithm (HEDA_CS) to solve the NIPFSP with the total tardiness criterion minimization. The problem model is built on the basis of the starting and ending time point of each job. A discrete solution representation method is applied in HEDA_CS to increase the operation efficiency. A novel probability matrix build method is also designed within the knowledge of the processing time matrix. The partially-mapped crossover operation works effectively during the CS phase. A suitable knowledge-based local search is also designed in the HEDA_CS to balance the exploitation and exploration. Finally, many simulations based on the new hard Ruiz benchmarks are conducted. Computational results demonstrate the effectiveness of the proposed HEDA_CS.