Using Genetic Algorithms for Parallel Machines Multi-Objective Scheduling Problems with Families and One Resource Constrained
一种求解带资源约束的并行机器多目标调度问题的遗传算法

Multi-objective scheduling on parallel machines with families and one resource constrained is considered. The objectives are total tardiness and maximum make-span. This paper proposes genetic algorithms using tournament selection, niche count, and violation degree to solve this problem. The computational results from random orders show that the genetic algorithms are more efficient than rectified EDD,LPT, and SPT in solving the problem.