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

作者：Tyagi Satish K^*; Yang Kai; Tyagi Annu; Dwivedi Suren N

来源：Engineering Applications of Artificial Intelligence, 2011, 24(5): 866-879.

DOI：10.1016/j.engappai.2011.02.009

• Concurrent engineering
• Pre-communications
• Gaussian distribution
• Particle Swarm Optimization
• TVACs

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.

• 出版日期2011-8