نشریه پژوهش های نوین در تصمیم گیری
سال سوم شماره 3 (پاییز 1397)

Today, the most important aspect of product design is based on the needs and requirements of customers, therefore, the Quality Function Deployment (QFD) approach is one of the ways that is used to increase customer satisfaction. Due to the uncertainty and inaccuracy of the properties in the relationships, the fuzzy coefficients are often used in planning QFD. In the present study, the fuzzy linear regression approach is used to identify inaccurate and ambiguous functional relationships between customer requirements and engineering indicators. In this approach, for non-fuzzy data situation, the optimal values of the parameters would be determined based on the output set of the regression model so that it has a membership degree greater than or equal to h, which indicates how much fuzzy the output of the fuzzy regression model is being. In this study, the aim of using a fuzzy linear regression model is to identify the functional relationships in QFD to optimize h value in the industrial lama electronics industry. The results of this study indicate that the values of the range of coefficients in optimal h model, when compared to zero, give better data and increase the reliability of the system.

In this paper, we address the multi-skilled RCPSP with time-dependent resource capacities and generalized precedence relations between activities. In this problem, a set of multi-skilled workforces are required to execute project activities. Each worker is able to perform several skills. The availability of workforces is time-dependent due to holidays, weekends, sicknesses, etc. Therefore, in this study, a mathematical formulation is proposed for the multi-skilled RCPSP with time-dependent resource availabilities. The objective function of the model is minimization of project completion time. The proposed model in this study is an NP-Hard problem in the strong sense. Hence, we develop a new meta-heuristic algorithm based on harmony search algorithm to solve the proposed model. New crossover and mutation operators have been designed for the proposed method to produce diverse solutions and to prevent the proposed algorithm from converging to a local optima. Hence, the proposed method not only uses the common procedure in harmony search algorithm, but also it employs the proposed crossover and mutation operators to explore solution space more accurately. The generated solutions are all combined and the harmony memory is updated. The effectiveness of this method has been compared to particle swarm optimization (PSO) and genetic algorithm (GA) in solving 30 test problems. The results show that the proposed method has been superior in terms of multiple performance measures.

In this paper an integrated production and outbound distribution scheduling (IPODS) with vehicle routing problem (VRP) for multi customer situation in a supply chain is addressed. There are K orders (jobs) that have to be scheduled on a single machine and delivered to K customers. Each order has its own due date. The manufacturer delivers the orders in batches which have no capacity constraint. Delivering the products in batches reduces the delivery cost but it may increase the number of tardy jobs. No other research has been conducted on this problem yet. This problem is strongly NP-Hard. The objective is to minimize the sum of the total weighted number of tardy jobs and delivery costs. Also, in this paper, an MILP model and a Heuristic Algorithm (HA) for solving this problem are presented. Full factorial Computational test is performed for evaluation of these two methods. The obtained results on 3840 problems show that the heuristic algorithm is efficient for solved problem. Also we surveyed parameter's levels effect on CPLEX and heuristic performance by analysis of variance.

Today, the necessity of forming teams has become more important than ever and firms begin to concentrate on finding proper people with team skills. This is especially true in research and development (R&D) organizations that are critical for maintaining organizational innovation. Organizations rely on R&D teams to develop new technologies and products. Thus, the aim of this research is to select the best individuals as R&D team members. So far, several methods have been used to select members and mathematical modeling has been considered as an efficient approach. This research is an applied and descriptive – analytical research. For this purpose, the objective function is to choose individuals who earn the most points and decision variable is 0-1 if the candidate is selected or not. Individual characteristics of team members are derived from existing competency models. Individual weights will be obtained by using revised Simos and according to experts and Myers-Briggs Type Indicator will be employed to gain collaborative weights. Finally, Multi Objective Simulated Annealing algorithm will be used to solve the problem. The modeling was used for team member selection of one of the largest Keyson Company R&D projects.

Leather industry is an old and traditional industry in Iran. Iran is one of the oldest leather manufacturers in the world. Clothes and leather industries have been discovered in Iran show that Iran leather industry goes back more than 3000 years ago. However, when Iran has a historical background in leather industry and animal skin in Iran is genetically one of the best skin in the world, unfortunately, this industry has failed to achieve proper place in the international markets. Iranian leather companies lost thier competitiveness power and their survival is countered by threats. These threats has caused only about 25 percent of leather factories and workshops are active today. However, organizational resilience can lead to competitive advantage of organizations and reinforcement their survival in the face of crisis. This article firstly designes a framework for organizational resilience, and then evaluates the resilience situations of three active companies in the leather industry. The results show that these companies are very weak in resilience situation.

This paper addresses a new mathematical model of economic lot sizing and scheduling problem in distributed permutation flow shop problem with a number of non-identical factories and machines that have not been considered in previous articles. For this purpose, different products must be distributed between the factories then assignment of products to factories and sequencing of the products assigned to each factory has to be derived. The objective is to minimize the sum of setup costs, work-in-process inventory costs, finished products inventory costs per unit of time and total production cost that consists of cost of unbalanced assignment of products between factories. Since the proposed model is NP-hard, an efficient hybrid Vibration Damping Optimization with Imperialist Competitive Algorithm and Simulated Annealing are considered to solve the model. In addition, Genetic Algorithm and VDO are used for comparison. In order to determine the best value of algorithms parameters that result in a better solution, a fine-tuning procedure according to Response Surface Methodology is executed. The results show that the HVDO has a better performance in achieving the minimum goal in this problem.

One of the methods widely used by researchers to analyze the risk of maintenance operations is Failure Modes and Effects Analysis (FMEA). However, the conventional approach of the FMEA faces serious drawbacks to rank equipment and failure modes. The purpose of this paper is to dynamically rank equipment in an Interval-Valued Intuitionistic Fuzzy environment to identify critical equipment, So that the main drawbacks of the conventional FMEA are eliminated. To this end, we present the Interval-Valued Intuitionistic Fuzzy condition based dynamic weighing method (IVIF-CBDW). In following, by improving the interval-valued intuitionistic fuzzy power weight Heronian aggregation (IVIFPWHA) operator and improving the approach of multi attributive border approximation area comparison (MABAC) method, these two improved methods by Interval-Valued Intuitionistic Fuzzy condition based dynamic weighing method (IVIF-CBDW) have been merged and a robust FMEA model has been proposed in which the main drawbacks of the conventional FMEA have been eliminated. In order to prove its applicability, this model was used in a case study to rank the equipment of a HL5000 crane barge. Finally, the results are compared with the traditional FMEA methods. It is indicated that the proposed model is much more flexible and provides more rational results.

In this paper, a heuristic solution approach to the single source capacitated facility location problem is considered. As a first step, a local search method is designed to perform quick simple moves in the solution structure. Then, the greedy manner of the local search is combined by Simulated Annealing meta-heuristic. Such a careful combination would allow escaping local optima with the aim of more diversified search capabilities. The method, then makes use of acceleration mechanisms to enhance search process. Here, we combine the algorithm with two different acceleration mechanisms namely consecrating mechanism and parallelizing mechanism. Such a combination will define two different versions of the mentioned search strategy based on simulated annealing meta-heuristic. Computational results obtained over the existing standard benchmark instances, not only demonstrate the superiority of the proposed method over the best existing ones, but also announce the method as an effective practical tool to tackle the problem.