An improved bat optimization algorithm to solve the tasks scheduling problem in open shop

作     者：Shareh, Morteza Babazadeh Bargh, Shirin Hatami Hosseinabadi, Ali Asghar Rahmani Slowik, Adam 

作者机构：Islamic Azad Univ Babol Branch Dept Comp Engn Babol Sar Iran Babol Univ Med Sci Babol Sar Iran Islamic Azad Univ Young Researchers & Elite Club Ayatollah Amoli Branch Amol Iran Koszalin Univ Technol Dept Elect & Comp Sci Koszalin Poland 

出 版 物：《NEURAL COMPUTING & APPLICATIONS》 (神经网络计算与应用)

年 卷 期：2021年第33卷第5期

页      面：1559-1573页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Open shop Scheduling Makespan Bat algorithm Heuristic functions 

摘      要：The open shop scheduling problem involves a set of activities that should be run on a limited set of machines. The purpose of scheduling open shops problem is to provide a timetable for implementation of the entire operation so that the total execution time is reduced. The tasks scheduling problem in open shops is important in many applications due to the arbitrariness of the processing sequence of each job and lack of a prioritization of its operations. This is an NP-hard problem and obtaining an optimal solution to this problem requires a high time complexity. Therefore, heuristic techniques are used to solve these problems. In this paper, we investigate the tasks scheduling problem in open shops using the Bat Algorithm (BA) based on ColReuse and substitution meta-heuristic functions. The heuristic functions are designed to increase the rate of convergence to the optimal solution. To evaluate the performance of the proposed algorithm, standard open shop benchmarks were used. The results obtained in each benchmark are compared with those of the previous methods. Finally, after analyzing the results, it was found that the proposed BA had a better performance and was able to generate the best solution in all cases.