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A New Multi-objective Algorithm For A Project Selection Problem

机译:解决项目选择问题的新多目标算法

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摘要

Project selection problem is an incessant problem, which every organization face. It, in fact, plays a key role in prosperity of the company. Meta-heuristic methods are the well-reputed methods which have been employed to solve a variety of multi-objective problems forming the real world problems. In this paper, a new multi-objective algorithm for project selection problem is studied. Two objective functions have been considered to maximize total expected benefit of selected projects and minimize the summation of the absolute variation of allotted resource between each successive time periods. A meta-heuristic multi-objective is proposed to obtain diverse locally non-dominated solutions. The proposed algorithm is compared, based on some prominent metrics, with a well-known genetic algorithm, i.e. NSGA-II. The computational results show the superiority of the proposed algorithm in comparison with NSGA-II.
机译:项目选择问题是每个组织都必须解决的一个不间断的问题。实际上,它对公司的繁荣起着关键作用。元启发式方法是公认的方法,已被用来解决构成现实世界问题的各种多目标问题。本文针对项目选择问题研究了一种新的多目标算法。已经考虑了两个目标函数,以最大化所选项目的总预期收益,并最小化每个连续时间段之间分配资源的绝对变化之和。提出了一种元启发式多目标算法,以获得各种局部非支配的解决方案。基于一些突出的指标,将提出的算法与著名的遗传算法NSGA-II进行比较。计算结果表明,与NSGA-II相比,该算法具有优越性。

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