A hybrid differential evolution algorithm for the multi-objective reentrant job-shop scheduling problem
Bin Qian, Z. H. Li, Rong Hu, Cen Zhang · 2013
This paper proposes a hybrid differential evolution algorithm (HDE) for solving the multi-objective reentrant job-shop scheduling problem (MRJSSP) with total machine idleness and maximum tardiness criteria. Firstly, a so-called reentrant-smallest-order-value (RSOV) rule is presented to convert the continuous values of individuals in DE to job permutations. Secondly, after the global search based on DE, a problem-dependent local search with different neighborhoods is presented to emphasize local search. Since both global and local search are well balanced, HDE has the ability to obtain good results. Simulation results and comparisons show the effectiveness of the proposed algorithm.