An improved genetic algorithm for solving flexible job shop

According to the characteristics of flexible job shop scheduling (FJPS), a mathematical model was established minimize maximum completion time, and an improved genetic algorithm proposed solve problem. A variety heuristic methods are used improve quality initial solution. The parallel double-chain encoding is designed optimal insertion method Two crossover methods, namely IPOX multi-point crossover, adopted inherit excellent genes from parent generation balance global development ability algorithm. In different coding layers, variation were maintain diversity population. local enhanced by variable neighborhood search. Finally, solving Brandimarte standard example comparing with other algorithms, feasibility effectiveness verified.