OPTIMIZATION OF RESOURCE‐CONSTRAINED PROJECT SCHEDULES BY SIMULATED ANNEALING AND VARIABLE NEIGHBORHOOD SEARCH
研究了资源受限的项目调度问题，通过优先级列表编码和模拟退火、变邻域搜索等算法寻找最优调度方案，并基于项目调度库数据验证了效果。
Applications of information technologies are often related to making some schedules, timetables of tasks or jobs with constrained resources. In this paper we consider job scheduling and optimization algorithms related to resources, time and other constraints. Schedule optimization procedures, based on schedule coding by priority list of jobs, are created and investigated. Optimal priority list of jobs is found by approaching algorithms of local and global search, namely, random search and simulated annealing methods with the variable neighborhood, defined by the decoding procedure applied. Computational results with testing data from project scheduling Library are given.