一种用于安排重复性项目的双目标优化技术

Q3 Decision Sciences
Jeeno Mathew, Brijesh Paul
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引用次数: 0

摘要

重复项目是指同一类型的工作/活动在不同的地点或地点重复进行的项目。对于每一个此类项目,每个活动都有不同的船员选择,选择适合每个活动的最佳选择是一项艰巨的任务。在这些项目中,项目经理经常面临着找出与满足不同约束条件的最佳项目工期和支出相对应的最佳进度计划的任务。由于这类项目的计算复杂度很高,本研究提出了一种基于ABC算法的启发式方法,可以针对不同的约束条件给出满足上述目标的较好解。用精确解对该方法的性能进行了分析,结果表明,基于ABC算法的方法给出了显著的高质量解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A bi-objective optimisation technique for scheduling repetitive projects
Repetitive projects are projects in which the same type of works/activities gets repeated in different locations or sites. For each of this type of projects, different crew options are available for each activity and selecting the best option corresponding to each activity is a difficult task. Project managers in these projects are often faced with the task of finding out the best schedule corresponding to the optimum project duration and expenditure which will satisfy different constraints. Since the computational complexity is very high in these types of projects, an ABC algorithm-based heuristic methodology is developed in this study, which can give good solutions for satisfying the above mentioned objectives with respect to different constraints. The proposed methodology's performance is analysed with exact solutions and the results show that an ABC algorithm-based methodology gives significantly good quality solutions.
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来源期刊
International Journal of Information and Decision Sciences
International Journal of Information and Decision Sciences Business, Management and Accounting-Management of Technology and Innovation
CiteScore
1.90
自引率
0.00%
发文量
13
期刊介绍: In today''s fast-paced business environment, even with an abundance of information, decision-making can be complex and slow. As floods of data emerge, effective information processing is sought as a panacea. With the ever-present spectre of uncertainty, sound decisions are key. As a consequence of the various conflicts/dilemmas, employment of efficient data management leading to better decision-making is the goal. Organisations must employ effective information management/decision-making processes at each critical stage of their functions. IJIDS addresses the issues involved in this. Topics covered include: -AHP or DEA -Behavioural sciences, psychology, sociology -Business intelligence, economics -Computing and decision sciences, data-driven decision making -Decision making in social setting, under uncertainty, with multimedia -Decision support systems/software -Decision theory, decision trees, MCDM -Ethical decision making, group decision making, software -Fuzzy information processing, game theory, grid analysis, informatics, IT -Intelligent agent technologies, neural networks, OLAP -Knowledge discovery in databases, web search, scenario/system analysis -Mathematics of decision sciences, decision making methods/styles -Perspectives of decision making, robust decisions, morphological analysis -Political/public decision making -Risk management, statistics
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