Abstract
Prior studies are lacking which address permutation flow shop scheduling problems and hybrid flow shop scheduling problems together to help firms find the optimized scheduling strategy. The permutation flow shop scheduling problem and hybrid flow shop scheduling problems are important production scheduling types, which widely exist in industrial production fields. This study aimed to acquire the best scheduling strategy for making production plans. An improved fireworks algorithm is proposed to minimize the makespan in the proposed strategies. The proposed improved fireworks algorithm is compared with the fireworks algorithm, and the improvement strategies include the following: (1) A nonlinear radius is introduced and the minimum explosion amplitude is checked to avoid the waste of optimal fireworks; (2) The original Gaussian mutation operator is replaced by a hybrid operator that combines Cauchy and Gaussian mutation to improve the search ability; and (3) An elite group selection strategy is adopted to reduce the computing costs. Two instances from the permutation flow shop scheduling problem and hybrid flow shop scheduling problems were used to evaluate the improved fireworks algorithm’s performance, and the computational results demonstrate the improved fireworks algorithm’s superiority.
Highlights
Solving scheduling problems is a topic in the optimization field [1]
The original fireworks algorithm, particle swarm optimization (PSO), and the whale optimization algorithm were used to test the performance of improved fireworks algorithm (IFWA) and experimental results are presented as follows
The results prove that the IFWA has an excellent ability to deal with the hybrid flow shop scheduling problem (HFSP)
Summary
Solving scheduling problems is a topic in the optimization field [1]. There are scheduling problems in all walks of life, such as medical resource allocation, power system scheduling, wireless network optimization, and electric vehicle scheduling [2,3,4,5,6]. The permutation flow shop scheduling problems (PFSP) is a type of typical combinatorial optimization problem that exists widely in the field of industrial automation [9]. It is shown that the FSPs belong to a class of NP-hard problems when the scale is more than three and the optimization algorithms with polynomial time have not yet been found [14]. For these typical scheduling problems, it is difficult to obtain satisfactory results by the traditional optimization methods. An improved fireworks algorithm (IFWA) is put forward for enhancing the performance of FWA and solving the two scheduling problems.
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