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Discrete stochastic multi-criteria decision-making (MCDM) can be used to handle many real-life decision-making problems. The Evaluation Based on Distance from Average Solution (EDAS) is a new and efficient MCDM method. The desirability of alternatives in this method is determined based on distances of them from an average solution. Because the average solution is determined by an arithmetic mean in this method, the EDAS method can be efficient for solving stochastic problems. In this paper, a stochastic EDAS method is proposed to handle problems in which the performance values of alternatives on each criterion follow the normal distribution. Based on the proposed method, we can obtain optimistic and pessimistic appraisal scores for evaluation of alternatives and consider the uncertainty of decision-making data. We present a graphical example to illustrate the proposed method and a practical example of performance evaluation of bank branches to show the applicability of it. According to the analyses made, the proposed method is efficient and the results are valid. [ABSTRACT FROM AUTHOR]

The assessment of Third-Party Logistics (3PL) provider becomes an important issue for enterprises trying to achieve operational efficiency and customer service improvement as well as capital expenditure and logistics costs reduction. It can be said that evaluation and selection of an appropriate 3PL provider is a kind of Multi-Criteria Decision-Making (MCDM) problem. Uncertainty is an unavoidable part of information in the decision-making process. Interval Type-2 Fuzzy Sets (IT2FSs) are very flexible to model the uncertainty of the MCDM problems. In this study, a new integrated approach based on the CRiteria Importance Through Inter-criteria Correlation (CRITIC) and Weighted Aggregated Sum Product ASsessment (WASPAS) methods is proposed to evaluate 3PL providers with IT2FSs. In the proposed approach, objective weights resulted from the CRITIC method are combined with subjective weights expressed by decision-makers (DMs) to determine more realistic weights for criteria. A computational study is performed to illustrate the proposed approach and the applicability of it. In addition, a sensitivity analysis is carried out using different sets of criteria weights to demonstrate the stability of the proposed approach. The results show the stability of ranking results and prove the efficiency of the proposed approach to handle MCDM problems with IT2FSs. [ABSTRACT FROM AUTHOR]

One of the important activities of a company that can increase its competitiveness is market segment evaluation and selection (MSE/MSS). We can usually consider MSE/MSS as a multi-criteria decision-making (MCDM) problem, and so we need to use an MCDM method to handle it. Uncertainty is one of the important factors that can affect the process of decision-making. Fuzzy MCDM approached have been designed to deal with the uncertainty of decision-making problems. In this study, a fuzzy extension of the CODAS (COmbinative Distance-based ASsessment) method is proposed to solve multi-criteria group decision-making problems. We use linguistic variables and trapezoidal fuzzy numbers to extend the CODAS method. The proposed fuzzy CODAS method is applied to an example of market segment evaluation and selection problem under uncertainty. To validate the results, a comparison is performed between the fuzzy CODAS and two other MCDM methods (fuzzy EDAS and fuzzy TOPSIS). A sensitivity analysis is also carried out to demonstrate the stability of the results of the fuzz CODAS. For this aim, ten sets of criteria weights are randomly generated and the example is solved using each set separately. The results of the comparison and the sensitivity analysis show that the proposed fuzzy CODAS method gives valid and stable results. [ABSTRACT FROM PUBLISHER]

The redundancy allocation problem (RAP) has been studied for many different system structures, objective functions, and distribution assumptions. In this paper, we present a problem formulation and a solution methodology to maximize the system steady-state availability and minimize the system cost for the repairable series-parallel system designs. In the proposed approach, the components' time-to-failure (TTF) and time-to-repair (TTR) can follow any distribution such as the Gamma, Normal, Weibull, etc. We estimate an approximation of the steady-state availability of each subsystem in the series-parallel system with an individual meta-model. Design of experiment (DOE), simulation and the stepwise regression are used to build these meta-models. Face centred design, which is a type of central composite design is used to design experiments. According to a max-min approach, obtained meta-models are utilized for modelling the problem alongside the cost function of the system. We use the augmented "-constraint method to reformulate the problem and solve the model. An illustrative example which uses the Gamma distribution for TTF and TTR is explained to represent the performance of the proposed approach. The results of the example show that the proposed approach has a good performance to obtain Pareto (near-Pareto) optimal solutions (system configurations). [ABSTRACT FROM AUTHOR]

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This paper presents a technique based on discrete-event simulation and response surface methodology to model and then optimize the schedule of subway train travels. The aim of this study is to find appropriate headways-time intervals between the travels of two consecutive trains-at different hours in order to optimize average passenger travel time and rate of carriage fullness. For physical reasons and the observance of safety standards, an increase in the train speed in order to decrease average passenger travel time may not exceed some specified limits. One of the ways to decrease this average is to appropriately adjust headways of trains in the schedule. For this purpose, a metamodel of multinomial type is fitted to the data obtained from simulation tests to describe the relation between input variables (headways) and output variables (average passenger travel time in system and carriage fullness rate), and then optimal combinations of input variables are obtained using a weighed metric method and sequential quadratic programming. [ABSTRACT FROM AUTHOR]

The location-allocation problem is one of the effective and efficient decision-making model in association with Facility Design topic. The requirements related to establishment and facility location selection, according to slightly criteria, is called locating. The severity of the damage caused by lack of proper locating as obvious and in many cases, its damages are irreparable. Among these cases, is locating of medical emergency services that the damages are fatal and irreparable. In this research, in order to locate the Assistance centers (emergency services) in district six of Tehran, the synthetic model of set covering problem and multi objective planning have been used. The objectives of maximizing the whole covered population and minimizing the whole transportation distances from demand locations to allocated servers, were taken into consideration. After coding the model via incremental simulated annealing algorithm in MATLAB software, final ranking of options has been done by utilizing REGIME technique. The conclusions showed that districts 4 (Yousef Abad - Amir Abad), 8 (Shariati Sindokht), 9 (Jahad Square), 12 (Behjat Abad), and 17 (Valiasr Square) are chosen as proper locations to allocate unreach centers. [ABSTRACT FROM AUTHOR]

Dynamic nature of global business makes it necessary for supply chains to be adaptable to changes. Also, complexities of the working environment and increasing competition in different industries have led to unstableness of the competitiveness factors. Creating and maintaining competitiveness need capabilities which create value for costumers based on the organization capacities. In the present study, a model of supply chain resilience is presented for competitiveness in Iranian automotive companies. It is expected that by its application, automobile firms not only have an effective method for controlling incidents, but also get to competitiveness. For this purpose, first by extensive review of the literature, a preliminary conceptual framework was extracted for supply chain resilience in order to create competitiveness. Then, using experts' views (Delphi method), interview, and doing the survey, the research model was formed and finalized based on the conditions of Iranian automobile industry. The results of the study showed that Iranian automobile firms can create the required flexibility for encountering the most important vulnerabilities of the firms by creating or improving capabilities like flexibility in sourcing, efficiency, security, flexibility in fulfillment, adaptability, and collaboration, and then using these opportunities they create competitiveness. The vulnerabilities of the firms include things like exchange and price fluctuations, international sanctions, weakness in know-how, low quality of the products, and weak services. [ABSTRACT FROM AUTHOR]