Variable parameters quantum-inspired evolutionary algorithm and its application in permutation flow-shop scheduling problem

Aiming at the solution for permutation flow shop scheduling, a Simple Quantum-inspired Evolutionary Algorithm (SQEA) was improved to design a Variable Parameters Quantum-inspired Evolutionary Algorithm (VP-QEA), and to solve the permutation flow shop scheduling problem with objective of makespan. The schedule of jobs was represented by polar angles of quantum bits, which could cut the length of quantum chromosome. The mutation rate and number of local search iterations were changed in the computation process to enhance the ability of globally searching and locally optimization, and achieve the preferable globally optimal solutions. VP-QEA was used to solve some Benchmark problems of permutation flow shop scheduling, and the numerical simulation showed the effectiveness and efficiency of the proposed algorithm.