Bi-objective supply chain problem using MOPSO and NSGA-II

The increase competition and decline economy has increased the relevant importance of having reliable supply chain. The primary objective of many supply chain problems is to reduce the cost of services and, at the same time, to increase the quality of services. In this paper, we present a multi-level supply chain network by considering multi products, single resource and deterministic cost and demand. The proposed model of this paper is formulated as a mixed integer programming and we present two metaheuristics namely MOPSO and NSGA-II to solve the resulted problems. The performance of the proposed models of this paper has been examined using some randomly generated numbers and the results are discussed. The preliminary results indicate that while MOPSO is able to generate more Pareto solutions in relatively less amount of time, NSGA-II is capable of providing better quality results

An empirical study to determine the critical success factors on customer retention: A case study of Iranian banking sector

One of the most important strategic issues for any enterprise is to create and deliver superior value for its customers and provide enough evidences to convince them not to choose another competitive. In this study, we study the effects of customer value, customer satisfaction and customer loyalty on customer retention. The results indicate that all aspects of the customer value have positive relationships with customer satisfaction but only emotional value has a positive and direct relationship with customer loyalty. The study confirms that while none of customer value aspects has direct and positive relationship with customer retention, both customer satisfaction and customer loyalty positively and directly affect customer retention

A hybrid of fuzzy FMEA-AHP to determine factors affecting alternator failure causes

This paper presents a method to determine factors influencing alternator failure causes. Failure Mode and Effects Analysis (FMEA) is one of the first systematic techniques for failure analysis based on three factors including Probability (P), Severity (S) and Detection (D). Traditional FMEA method considers equal weights for all three factors, however, in read-world cases; one may wish to consider various weights. The proposed study develops a mathematical model to determine optimal weights based on analytical hierarchy process technique. The implementation of the proposed study has been demonstrated for a read-world case study of alternator failure causes

Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using GRASP method

Cross docking play an important role in management of supply chains where items delivered to a warehouse by inbound trucks are directly sorted out, reorganized based on customer demands, routed and loaded into outbound trucks for delivery to customers without virtually keeping them at the warehouse. If any item is held in storage, it is usually for a short time, which is normally less than 24 hours. The proposed model of this paper considers a special case of cross docking where there is temporary storage and uses GRASP technique to solve the resulted problem for some realistic test problems. In our method, we first use some heuristics as initial solutions and then improve the final solution using GRASP method. The preliminary test results indicate that the GRASP method performs better than alternative solution strategies

A discount ordering strategy in two-level supply chain: A case study of textile industry

Supplier selection, inventory management and optimal lot sizing has been one of the most important issues in many industries especially in production planning issues associated with texture industry. The proposed model of this paper first introduces an algorithm to choose the best supplier and it determines the optimal lot size using discount strategy. The proposed model of this paper considers different influencing factors such as location, quality of materials, cost, and mutual trust for supplier selection, determines their relative importance weights and then a discounting method is used to determine the ordering lot-size. The preliminary results indicate that the proposed model of this paper can be implemented in texture industry, very efficiently since the ordering discount policy is not sensitive to changes on inventory holding and setup expenditures

Multi-objective group scheduling with learning effect in the cellular manufacturing system

Group scheduling problem in cellular manufacturing systems consists of two major steps. Sequence of parts in each part-family and the sequence of part-family to enter the cell to be processed. This paper presents a new method for group scheduling problems in flow shop systems where it minimizes makespan (Cmax) and total tardiness. In this paper, a position-based learning model in cellular manufacturing system is utilized where processing time for each part-family depends on the entrance sequence of that part. The problem of group scheduling is modeled by minimizing two objectives of position-based learning effect as well as the assumption of setup time depending on the sequence of parts-family. Since the proposed problem is NP-hard, two meta heuristic algorithms are presented based on genetic algorithm, namely: Non-dominated sorting genetic algorithm (NSGA-II) and non-dominated rank genetic algorithm (NRGA). The algorithms are tested using randomly generated problems. The results include a set of Pareto solutions and three different evaluation criteria are used to compare the results. The results indicate that the proposed algorithms are quite efficient to solve the problem in a short computational time

An empirical survey to investigate quality of men's clothing market using QFD method

One of the most important techniques on improving customer satisfaction in clothing and textile industry is to increase the quality of goods and services. There are literally different methods for detecting important items influencing clothing products and the proposed model of this paper uses quality function deployment (QFD). The proposed model of this paper designs and distributes a questionnaire among some experts to detect necessary factors and using house of quality we determine the most important factors impacting the customer's clothing selection. The proposed study of this paper focuses men who are 15 to 45 years old living in Yazd/Iran. The brand we do the investigation sells the products in three shopping centers located in this city. We have distributed 100 questionnaires and collected 65 properly filled ones. Based on the results of our survey, suitable design, printing and packaging specifications, necessary requirements, optimization of production planning and appropriate sewing machine setting are considered as the most important characteristics influencing the purchase of a clothing products

An application of fuzzy TOPSIS for identifying and analyzing black spots suburban areas

Nowadays, traffic safety is one of the primary principles of traffic engineering and transportation planning. Road accidents have been major problems that cause human losses, social and economic challenges. The first step to improve road traffic safety is to identify black spots, which preserve high potential of road accidents. Therefore, identifying, analyzing, prioritizing and refining these places play important role in improving transportation safety. This paper applies fuzzy Technique for Order Preference by Similarity to Ideal (TOPSIS) for ordering different black spots for a case study of highway between two cities of Qazvin and Saveh, Iran. The study performs the ranking based on two categories of tangent distance and horizontal curve. The ranking is performed according to Roadway width, Shoulder width, Traffic volume, Percentage of vehicle, Load and utility, Network access, The number of horizontal curves and Equivalent Property Damage Only (EPDO). The results are compared with frequencies of incidents and analyzed

A GRASP model in network design for two-stage supply chain

We consider a capacitated facility location problem (CFLP) which contains a production facility and distribution centers (DCs) supplying retailers' demand. The primary purpose is to locate distribution centres in the network and the objective is the minimization of the sum of fixed facility location, pipeline inventory, safety stock and lost sales. We use Greedy randomized adaptive search procedures (GRASP) to solve the model. The preliminary results indicate that the proposed method of this paper could provide competitive results in reasonable amount time

Management Science Letters An empirical study to determine the critical success factors on customer retention: A case study of Iranian banking sector

One of the most important strategic issues for any enterprise is to create and deliver superior value for its customers and provide enough evidences to convince them not to choose another competitive. In this study, we study the effects of customer value, customer satisfaction and customer loyalty on customer retention. The results indicate that all aspects of the customer value have positive relationships with customer satisfaction but only emotional value has a positive and direct relationship with customer loyalty. The study confirms that while none of customer value aspects has direct and positive relationship with customer retention, both customer satisfaction and customer loyalty positively and directly affect customer retention