Competitiveness of any manufacturing industry depends on its ability to respond quickly to market niches and to produce a variety of high-utility products at relatively low costs. The promising tool to achieve aforesaid goals is the development of an efficient product family design strategy. The collection of shared components across the product family is termed as a platform that allows the saving in additional cost. Unfortunately, a single platform is advantageous only up to a certain extent; firms have sensed the requirement of multiple platforms. In this context, this paper deals with the exploration of product family design and multiple-platform architecture with a view to maximize the overall utility and to minimize the total production cost. This multiobjective problem has two conflicting and incommensurate objectives; therefore, a fuzzy goal programming model is adopted for modeling. The adoption of fuzzy goal programming model aids in combining the two objectives as well as captures the inherent uncertainty involved in decision making. The problem is formulated as a mixed integer program, and, additionally, random search optimization techniques, namely, genetic algorithm, simulated annealing, and Tabu search are being used to resolve the underlying issues. Moreover, in order to illustrate the proposed framework, a hypothetical case study-a family of mobile phones-is considered. Extensive experiments are performed on the underlying case study, and computational results are reported to validate the efficacy of multiple platforms over the single platform.Index Terms-Conjoint analysis, fuzzy goal programming, multiple-platform architecture, product family design, random search optimization techniques (RSOTs).
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