Jaya algorithm using weighted sum approach for the multi-objective next release problem

Pavitdeep Singh, M. Bhamrah, Jatinder Kaur
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引用次数: 1

Abstract

Software requirements gathering and selection is primarily the first and most important step during in the development of a software product. These new set of requirements drives the next set of functionalities/ features for the product. However, there is always a necessity to select the right set of requirement which fulfills the customer satisfaction and deliver these changes within the defined budget limits. The complexity of selecting the new requirements increases with the inter-dependency of various requirements defined. In this paper, we use a Jaya based optimization technique using weighted sum approach to solve the multi-objective next release problem (MONRP). In this approach, classic bi-objective NRP comprising the conflicting objectives e.g. maximizing global satisfaction and minimizing the cost (total development effort) are reduced to single objective by assigning different weights to each objective. The proposed technique has been successfully applied to a public dataset instance provided in various literature of NRP. The simulation results are compared with various well known variants of GDE3 algorithm for solution accuracy.
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Jaya算法采用加权和法求解多目标下一个放行问题
软件需求的收集和选择主要是软件产品开发过程中第一步也是最重要的一步。这些新的需求集驱动了产品的下一组功能/特性。然而,总是有必要选择满足客户满意度的正确需求集,并在定义的预算限制内交付这些更改。选择新需求的复杂性随着定义的各种需求的相互依赖性而增加。本文采用一种基于Jaya的优化技术,利用加权和方法求解多目标下一个发布问题。在这种方法中,经典的双目标NRP包括冲突的目标,例如最大化整体满意度和最小化成本(总开发工作量),通过为每个目标分配不同的权重,减少到单个目标。所提出的技术已成功应用于NRP的各种文献中提供的公共数据集实例。仿真结果与各种已知的GDE3算法的解精度进行了比较。
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