A Solution to Resource-Constrained Project Scheduling Problem: Based on Ant Colony Optimization Algorithm

Yongbo Yuan, Kai Wang, Le Ding
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引用次数: 3

Abstract

Ant Colony Optimization (ACO) is a popular-based, artificial agent, general-search technique for the solution of difficult combinatorial problems. This paper presents a solution to the Resource-Constraint Project Scheduling Problem based on ACO algorithm. The method considers the quantified duration and resource as the heuristic information to calculate the accurate state transition probability and finally reaches the scheduling optimization. The described ACO algorithm is tested on a sample case taken from the literature and the parameters in ACO are determined by tests. The computational results validate the effectiveness of the proposed algorithm.
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基于蚁群优化算法的资源约束项目调度问题求解
蚁群优化是一种基于人工智能的通用搜索技术,用于求解复杂的组合问题。提出了一种基于蚁群算法的资源约束型项目调度问题的求解方法。该方法将量化的时间和资源作为启发式信息,计算出准确的状态转移概率,最终达到调度优化。本文通过一个实例对蚁群算法进行了测试,并通过测试确定了蚁群算法中的参数。计算结果验证了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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