A Dynamic Opposite Learning Assisted Grasshopper Optimization Algorithm for the Flexible JobScheduling Problem

Abstract

Job shop scheduling problem (JSP) is one of the most difficult optimization problems in manufacturing industry, and flexible job shop scheduling problem (FJSP) is an extension of the classical JSP, which further challenges the algorithm performance. In FJSP, a machine should be selected for each process from a given set, which introduces another decision element within the job path, making FJSP be more difficult than traditional JSP. In this paper, a variant of grasshopper optimization algorithm (GOA) named dynamic opposite learning assisted GOA (DOLGOA) is proposed to solve FJSP. The recently proposed dynamic opposite learning (DOL) strategy adopts the asymmetric search space to improve the exploitation ability of the algorithm and increase the possibility of finding the global optimum. Various popular benchmarks from CEC 2014 and FJSP are used to evaluate the performance of DOLGOA. Numerical results with comparisons of other classic algorithms show that DOLGOA gets obvious improvement for solving global optimization problems and is well-performed when solving FJSP.

Solving the Flexible Job Shop Scheduling Problem Using a Discrete Improved Grey Wolf Optimization Algorithm

“…In this section, Fdata is used to test the performance of the proposed algorithm, and the results of the proposed DIGWO are compared with those of recent studies AIA, EPSO, MIIP and DOLGOA [31,55,67,68]. In order to eliminate randomness during the experiment, the results of 20 independent runs are shown in Table 15.…”

“…Feng et al suggested a dynamic opposite learning assisted grasshopper optimization algorithm (DOLGOA). The dynamic opposite learning (DOL) strategy is used to improve the utilization capability of the algorithm [31]. Li et al introduced a diversified operator im-perialist competitive algorithm (DOICA), which requires minimum makespan, total delay, total work and total energy consumption [32].…”

Adaptive Population NSGA-III with Dual Control Strategy for Flexible Job Shop Scheduling Problem with the Consideration of Energy Consumption and Weight

“…The manufacturing industry plays an indispensable role in the economic development and social construction of a country [9,10]. At the same time, the manufacturing industry is also an area where a country invests a tremendous amount of energy consumption [11,12].…”