计算机科学
运筹学
调度(生产过程)
启发式
净现值
遗传算法
位于
资源平衡
资源(消歧)
数学优化
项目管理
资源配置
系统工程
工程类
数学
人工智能
经济
机器学习
宏观经济学
计算机网络
生产(经济)
作者
M P Reshma Suresh,Pankaj Dutta,Karuna Jain
标识
DOI:10.1142/s0217595915500487
摘要
Scheduling multi-project is a complex decision making process. It involves the effective and timely allocation of resources to different projects. In the case of multi-project, resources are often transferred between the projects. It consumes both time and cost, when projects are situated in different geographic locations. As a result, the net present value (NPV) of multi-projects is significantly impacted by the resource transfer time. In this paper, a new genetic algorithm (GA) approach to the multi-project scheduling problem with resource transfer times is presented, where the NPV of all projects is maximized subject to renewable resource constraints. The paper also presents a heuristic approach using two phase priority rules for the same problem. We conduct a comprehensive analysis of 60 two-phase priority rules. The proposed GA approach is compared to the heuristic approach using the well-known priority rules. An extensive computational experiment is reported.
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