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Development of a fuzzy goal programming model for optimization of lead time and cost in an overlapped product development project using a Gaussian Adaptive Particle Swarm Optimization-based approach

机译:使用基于高斯自适应粒子群优化的方法开发用于优化重叠产品开发项目中的交货时间和成本的模糊目标规划模型

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The aim of this paper is to present a model-based methodology to estimate the optimal amount of overlapping and communication policy with a view to minimizing product development lead time and cost. In the first step of methodology, the underlying two factors are considered in order to formulate mathematically a multi-objective function for a complete product development project. To add these objectives, incommensurate in nature, a fuzzy goal programming-based approach is adopted as the second step. In order to attain the optimal solution of formulated objective function, this paper introduces a novel approach, "Gaussian Adaptive Particle Swarm Optimization" (GA-PSO), which is embedded with two beneficial attributes: (1) Gaussian probability distribution, and (2) Time-Varying Acceleration Coefficients strategy. An illustrative hypothetical example of mobile phones is detailed to demonstrate the proposed model-based methodology. Experiments are performed on an underlying example, and computational results are reported to support the efficacy of the proposed model.
机译:本文的目的是提出一种基于模型的方法来估计重叠和沟通策略的最佳数量,以最大程度地缩短产品开发的交付时间和成本。在方法的第一步中,考虑了潜在的两个因素,以便在数学上为一个完整的产品开发项目制定一个多目标函数。要添加本质上不相称的这些目标,则采用基于模糊目标规划的方法作为第二步。为了获得公式化目标函数的最优解,本文引入了一种新方法“高斯自适应粒子群优化”(GA-PSO),该方法具有两个有益的属性:(1)高斯概率分布;(2) )时变加速度系数策略。详细说明了手机的示例性假设示例,以演示所提出的基于模型的方法。在一个基础示例上进行了实验,并报告了计算结果以支持所提出模型的有效性。

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