Abstract
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.
Highlights
The scheduling and sequencing of operations is, the optimal allocation of limited resources to activities over time [1]
Finding an optimal applicable scheduling in this environment would help in order to execute the best policy in industries
A proposed bat algorithm is applied for solving open shop scheduling problem (OSSP)
Summary
The scheduling and sequencing of operations is, the optimal allocation of limited resources to activities over time [1]. The most important studies were carried out on heuristic algorithms by Brasel et al [20] who presented a comparative study of heuristic algorithms for OSP aimed at minimizing the average flow time They made comparisons for problems with up to 50 jobs and 50 machines. Hosseinabadi and Ahmadizar [25] proposed a HGA for the OSSP with the goal of minimizing the maximum completion time of the jobs In this algorithm, a special intersection operator is used to maintain the order of the machines and a strategy is used to avoid the search for unnecessary responses in the jump operator. Zhao et al [31] proposed a new method based on the water wave optimization algorithm (WWOA) to solve the no-wait flow shop scheduling problem (NW-FSSP).
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