A Hybrid Genetic Algorithm for Tasks Scheduling in Parallel Multiprocessor Systems
Yiwen Zhong, Jiangang Yang · Fudan xuebao. Ziran Kexue ban · 2004
It presents a new hybrid genetic algorithm (HGA) to solve the tasks scheduling problem in parallel multiprocessor systems. It uses the crossover of topological sort list to guarantee that each offspring is a feasible solution and the search space is a global one. In order to improve the convergence of GA, it uses greedy strategy to improve the fitness of one chromosome in the population in crossover operator, based on Lamarckian theory in the evolution. The simulation results show that the HGA produces encouraging results in terms of quality of solution and time complexity.