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Volume 20, Issue 1 (5-2009)

Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show the relations between essential components in complex systems. In this paper, a novel learning method is proposed to construct FCMs based on historical data and by using meta-heuristic: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). Implementation of the proposed method has demonstrated via real data of a purchase system in order to simulate the system’s behavior.
Sujit Kumar Jha,
Volume 23, Issue 3 (9-2012)

This paper presents an overview of new approaches in rapid product development in production networks from design points of view. The manufacturing industries are changing their focus to global sourcing as a means to improve performance and enhance competitiveness. Some partnerships created with this strategy improve product development through collaborative design. With the advent of e-Commerce, a new set of collaborative applications integrated to the firms’ IT infrastructure allow a direct interaction between the firm and its suppliers, having an impact of negotiations. The globalization of the market necessitates the reduction of time-to-market, mainly due to shorter product life cycle. The computing and communication have become indispensable in every aspect of product development and design. The paper describes the network that directly links designer capabilities and with customers and manufacturing division. The networks focuses the three major forces that will affect the design community, namely, speed of decision, expansion of scope and degree of concurrency. Due to evolution of production networks, it has become possible to obtain the mass production within a key short time, using emerging technology that affect the speed and efficiency of product development using a pool of efficient designers and product managers.
Mahdi Ruhparvar, Hamed Mazandarani Zadeh, Farnad Nasirzadeh,
Volume 25, Issue 2 (5-2014)

An equitable risk allocation between contracting parties plays a vital role in enhancing the performance of the project. This research presents a new quantitative risk allocation approach by integrating fuzzy logic and bargaining game theory. Owing to the imprecise and uncertain nature of players’ payoffs at different risk allocation strategies, fuzzy logic is implemented to determine the value of players’ payoffs based on the experience and subjective judgment of experts involved in the project. Having determined the players' payoffs, bargaining game theory is then applied to find the equitable risk allocation between the client and contractor. Four different methods including symmetric Nash, non-symmetric Nash, non-symmetric Kalai–Smorodinsky and non-symmetric area monotonic are implemented to determine the equitable risk allocation. To evaluate the performance of the proposed model, it is implemented in a pipeline project and the quantitative risk allocation is performed for the inflation risk as one of the most significant identified risks.

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