计算机系统应用可以供一作吗,一种求解车间作业调度的自适应混合遗传算法①-计算机系统应用.PDF...

2010 19 4

( 400044)

An Adaptive Hybrid Genetic Algorithm for Job Shop Scheduling Problems

TAO Si-Nan, FU Li, CAI Bin

(Department of Software Engineering, Chongqing University, Chongqing 400044, China)

Abstract: To overcome the shortcoming of the genetic algorithm and the tabu search algorithm for solving the job

shop scheduling problem, this paper proposes an adaptive genetic tabu algorithm. By adjusting the mutation

probability adaptively and putting the tabu search algorithm to the process of the genetic algorithm, the

improved genetic tabu algorithm promotes the rate in convergence and avoids such disadvantages as

premature convergence. Simulation experiments demonstrate that the proposed improved genetic tabu

algorithm is fast in convergence, and it does not get stuck at a local optimum easily.

Keywords: genetic algorithm; tabu search algorithm; job shop scheduling; mutation probability

(Job-Shop

Scheduling Problems) [1-4]

GA

NP Hard

1