Abstract
Research on Multi-Objective Hybrid Flow Shop Scheduling Problem With Dual Resource Constraints Using Improved Memetic Algorithm
Highlights
In order to reduce the costs, improve the production efficiency, and allocate the human resources effectively, based on the existing literature, this paper proposed a new memetic algorithm based on NSGA-II to solve the multi-objective hybrid flow shop scheduling problem (HFSP) with dual resource constraints aiming at minimizing the makespan, total tardiness time and workload balance of worker, in which the processing time is determined jointly by machine and worker
WORKS This paper mainly studies the hybrid flow shop scheduling problem with dual resource constraints of machines and workers, with the objective of minimizing the makespan, total tardiness time and workload balance of worker
The effectiveness of the proposed algorithm is evaluated by considering the benchmark problems
Summary
Taking the first gene in OS as an example, 1 represents job 1, and the corresponding operation is O11, machine 1 is used to process the operation O11, and worker 1 is selected to operate the machine 1. The decoding process is to select the right machine for each job and the right worker for each machine, determine the sequence of all operations and their starting and ending times, and obtain the objective functions value. Step 3: According to the machine and worker selected by the operation Oij, the processing time Pijkv of the operation is obtained. According to the above decoding process, considering various constraints of the problem, taking the chromosome in Figure 2 and the processing times in Table 1 as an example, the gantt charts obtained are shown, and the solution process of three objective functions is shown in (15) (16) (17).
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