International Journal of Industrial Engineering & Production Research

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In highly competitive industrial market, the concept of failure analysis is an unavoidable fact in complex industrial systems. Reliability of such systems not only depends on the reliability of each element of these systems, but also depends on occurrence of sequence of failures. In this paper, a novel approach to sequential failure analysis is proposed which is based upon fuzzy logic and the concept of Petri nets which is utilized to track all the risky behaviors of the system and to determine the potential failure sequences and then prioritizing them in order to perform corrective actions. The process of prioritizing failure sequences in this paper is done by a novel similarity measure between generalized fuzzy numbers. The proposed methodology is demonstrated with an example of two automated machine tools and two input/output buffer stocks.

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control of production processes in an industrial environment needs the correct setting of input factors, so that output products with desirable characteristics will be resulted at minimum cost. Moreover, such systems havetomeetset of qualitycharacteristicstosatisfycustomer requirements.Identifyingthemosteffectivefactorsindesignoftheprocesswhichsupportcontinuousandcontinualimprovement isrecentlydiscussedfromdifferentviewpoints.Inthisstudy, we examined the quality engineering problems in which several characteristics and factors are to be analyzed through a simultaneous equations system. Besides, the several probabilistic covariates can be included to the proposed model. The main purpose of this model is to identify interrelations among exogenous and endogenous variables, which give important insight for systematic improvements of quality. At the end, the proposed approach is described analytically by a numerical example.

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Customer service level is of prime importance in today competitive world and has various dimensions with delivery quality being one of the most important ones. Delivery quality has several parameters such as deliver time window options, time window size, etc. In this paper we focus on one of these parameters, namely time window setting. It has a direct impact upon customer satisfaction and business profit. On the other hand, delivery time windows affect routing and distribution costs. Generally, in the routing operation, time windows have been determined by customers or distributer and are considered as input parameters for the vehicle routing problem with time window (VRPTW) model. In this paper, a mathematical model is proposed for the integration of these two decisions in other words, in the present model, time window setting decisions are integrated with routing decisions. Then a column generation approach is employed to obtain the lower bounds of problems and to solve the problems, a quantum algorithm is proposed. Finally, the computational results of some instances are reported and the results of these approaches are compared. The results demonstrate the effectiveness of the quantum algorithm in solving this problem.

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Pricing and advertising are two important marketing strategies in the supply chain management which lead to customer demand’s increase and therefore higher profit for members of supply chains. This paper considers advertising, and pricing decisions simultaneously for a three-level supply chain with one supplier, one manufacturer and one retailer. The amount of market demand is influenced by pricing and advertising. In this paper, three well-known approaches in the game theory including the Nash, Stackelberg and Cooperative games are exploited to study the effects of pricing and advertising decisions on the supply chain. Using these approaches, we identify optimal decisions in each case for the supplier, the manufacturer and the retailer. Also, we compare the outcomes decisions among the mentioned games. The results show that, the Cooperative and the Nash games have the highest and lowest advertising expenditure, respectively. The price level in the Nash game is more than the Stackelberg game for all three levels, and the retailer price in the Stackelberg and Cooperative games are equal. The system has the highest profit in the Cooperative game. Finally, the Nash bargaining model will be presented and explored to investigate the possibilities for profit sharing.

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This paper addresses a production and outbound distribution scheduling problem in which a set of jobs have to be process on a single machine for delivery to customers or to other machines for further processing. We assume that there is a sufficient number of vehicles and the delivery costs is independent of batch size but it is dependent on each trip. In this paper, we present an Artificial Immune System (AIS) for this problem. The objective is to minimize the sum of the total weighted number of tardy jobs and the batch delivery costs. A batch setup time has to be added before processing the first job in each batch. Using computational test, we compare our method with an existing method for the mentioned problem in literature namely Simulated Annealing (SA). Computational tests show the significant improvement of AIS over the SA.

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In the current study, a dual-channel supply chain is considered containing one manufacturer and two retailers. It is assumed that the manufacturer and retailers have the same decision powers. A game-theoretic approach is developed to analyze pricing decisions under the centralized and decentralized scenarios. First, the Nash model is established to obtain the equilibrium decisions in the decentralized case. Then, the centralized model is developed to maximize the total profit of the whole system. Finally, the equilibrium decisions are discussed and some managerial insights are revealed. 

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This paper considers the advertising, pricing, and service decisions simultaneously to coordinate the supply chain with a manufacturer and a retailer. The amount of market demand is influenced by advertising, pricing and service decisions. In this paper, three well-known approaches to the game theory, including the Nash, the Stackelberg-retailer, and the cooperative game are exploited to study the effects of these policies on the supply chain. Using these approaches, we identify optimal strategies in each case for the manufacturer and the retailer. Then, we will compare the outcomes of each strategy thus developed. The results show that, compared with the Nash game, the Stackelberg-retailer game yields higher profits for the retailer, the manufacturer, and the whole system. The cooperative game yields the highest profits. Finally, the Nash bargaining model will be presented and explored to investigate the possibilities for profit sharing.

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Managing income is a considerable dimension in supply chain management in current economic atmosphere. Real world situation makes it inevitable not to design or redesign supply chain. Redesign will take place as costs increase or new services for customers’ new demands should be provided. Pricing is an important fragment of Supply chain due to two reasons: first, represents revenue based each product and second, based on supply-demand relations enables Supply chain to provide demands by making suitable changes in facilities and their capacities. In this study, Benders decomposition approach used to solve multi-product, multi-echelon and multi-period supply chain network redesign including price-sensitive customers.