A fuzzy hybrid decision-aid model for selecting partners in the design chain

Abstract

Due to reducing product life cycle and increasing product complexity, design chain management has become more important for industries to develop innovative products within a shorter lead-time. Selecting the design chain partners that is a key determinant of co-development success involves multiple selection criteria and constraints that are either qualitative or quantitative. Poor selection of design chain partners may cause higher development time and cost and less competitive products. This paper considers design chain partnership formation as a multi-criteria decision-making problem. Fuzzy set theory is used to represent information that is mostly imprecise and uncertain at this stage. A fuzzy hybrid decision-aid model that integrates a fuzzy multi-criteria outranking approach with a fuzzy integer programming model is proposed to tackle both qualitative and quantitative factors as well as the decision flexibility. A genetic algorithm approach is applied to select the set of partners that maximise the total performance score of the entire design chain and satisfy the constraints of target development time and cost at the same time. An example of mobile phone design chain is used to illustrate the developed concept

Partner selection model for design chain collaboration

“…Finally, they illustrated some managerial implications by performing simulated experiments. Wang and Lin (2006) proposed a fuzzy hybrid decision-aid model that integrated a fuzzy multi-criteria outranking approach with fuzzy integer programming. In their research, the objective of the model was to maximise the total performance score of the entire design chain subject to the development time and development cost constraints.…”

“…Wang and Lin (2006) refer to a Sony Ericsson example to show that the brand owner needs to be a system integrator to choose the right partners. The development process of a new product includes product planning, concept development, system design, detail design, testing, modification and production (Ulrich and Eppinger 2000).…”

“…How to integrate all resources into the design chain to face the highly competitive global market is the most important issue for the brand owner. As a result, the first step for brand owners is selecting the appropriate design partners (Handfield et al 1999, Deck and Strom 2002, Graves and Willems 2005, Wang and Lin 2006. Poor design partners may result in problems such as longer new product development time, higher cost, lower new product quality and a less competitive product (Wang and Lin 2006).…”

Using DEA and GA Algorithm for Finding an Optimal Design Chain Partner Combination

“…Chan et al [4] successfully solve the decision-making problem of supplier selection by FHA using cost, services, quality, and risk as criteria. Mikhailov [5] selects partners by FHA using financial stability, price, quality, customer services as criteria.Wang [6] uses fuzzy multicriteria xzoutranking method to first obtain performance evaluation for design chain partners by pair-wise comparison. Then, genetic algorithms can be applied to find the optimal combination under time and cost constraints.…”

Collaboration partner selection for city logistics planning under municipal freight regulations

“…Falsini et al [37] propose a logistics provider evaluation methodology based on AHP, DEA and linear programming using quality and reliability, speed of service, flexibility, costs, equipment, operators' safety, and environmental safeguard as evaluation criteria. Wang and Lin [38] propose a fuzzy hybrid decision-aid model based on fuzzy integer programming and genetic algorithm for selecting partners in the design chain. António and de Sousa [39] perform partner selection in virtual enterprises using tabu search and fuzzy TOPSIS.…”