نشریه پژوهش های نوین در تصمیم گیری
سال پنجم شماره 4 (زمستان 1399)

With increasing competition and the pace of change, companies will face with a crisis focus on exploiting existing capabilities or exploring new capabilities [1]. To adapting to the speed of change, Companies must adapt ideas or processes, which lead to the development of new products or services in emerging markets, and they must use current capabilities to exploit existing products and services [2]. So, in today's world, we need ambidextrous organizations with the ability of managing two kinds of incremental and radical changes simultaneously , and the ability of doing two opposite works at the same time, which are: stability of the status quo and change [3]. Therefore, the purpose of the present study is to identify the dimensions of ambidexterity, characteristics of an ambidextrous bank and provide a model for decision making on ambidexterity dimensions of a bank based on agent-based modeling according to market scenarios. This simulation model has been run in AnyLogic software.

In recent years, the use and implementation of the closed loop supply chain has been important because of the improvement in corporate profitability, environmental issues and sustainable development. This has led to a wider range of research and articles in this area. Therefore, studying the effective factors and their impact level is a better understanding of the design of a closed loop supply chain. The main focuses of this paper is on the planning of production capacity, taking into account customer behavior and service on the level of returns in the supply chain. The purpose of this paper is to clarify the effective variables and how they approach each other in order to achieve the goals of the chain. So, first, there is an overview of the subject literature and the key variables of some of the papers have been identified. In the next step, by drawing the causal and nonlinear diagrams, the relationships of the variables were examined together and then determined by the flow diagram, state variables, and accumulation locations in the chain. Finally, the model has been validated and validated using dynamic modeling tests such as sensitivity analysis, boundary condition testing, etc.

Hospital waste collection is one of the most important issues in urban service management. In this research, a mathematical model is developed to partition demographic areas in the hospital services system. In this model, regarding the needs of some service providers, the hierarchical structure of the partitions is considered. For this purpose, in a unified decision-making process, populations are divided into main partitions, and then, each one is divided into a number of sub-partitions. The purpose of this type of segmentation is to provide an ordered structure to control the service flow from the operational level to managerial level. Since partitioning is an NP-hard problem, it is necessary to use meta-heuristic algorithms to solve numerical examples in the real world. Here, genetic and gray wolf algorithms have been developed to solve large-scale problems. Despite the high efficiency of both algorithms, the computational results showed that the gray wolf algorithm is more capable in solving large-scale problems. The results of this study can be used as a management tool in solving types of population-based partitioning problems, including the problems of health systems.

Investigating the leanness of manufacturing systems, like other projects, is subject to some quantifiable and measurable components such as zero defect, zero transit time and so on, these coefficients and ratios can be extracted and calculated. In the present study, the operation of the concept of lean production and predicting the leanness of a production system is followed. With the help of this model, the degree of leanness of manufacturing companies can be assessed by focusing on management commitments and the level of leanness in the future can be predicted according to changes in effective indicators. The utility of the decision is calculated using the multiple linear combination form after examining the independence conditions of the indicators. Thus, the partial utility functions of all indices are considered simultaneously and assumed to be linear. In order to calculate the partial functions of experts in a textile company, help has been obtained. Finally, using the obtained model, the degree of leanness of the production system is presented in the form of a nonlinear mathematical function, thus providing a tool for better decision making in complex environmental conditions.

A mix of two or more strategies can be more helpful for players in future. This article introduces a series of games called Markovian Dynamic Games that if you consider the strategies of each player as a state, the player can select the same or another state depending on the situation in the next steps. The selecting each state in each step will be done with a specified probability. This probability is depending on the strategies of the competing players. In this study, a static two-player discrete game with Markov chain approach is considered that the probability of transfer is well-known, independent and is only influenced by the competitor's previous strategies. In this paper, the equilibrium points in markovian static games are evaluated and analyzed. Numerical examples are also presented for more explanations. In this paper, the difference between single-stage and multi-stage games in determining equilibrium points is shown. If a game is played in a multilevel manner, it is possible to design a discrete game as a Markov chain using the probability of transferring and considering the strategies of the game as a mode in each step, and by determining the probabilities of the specified chain, points He gained some balance. For this purpose, static games were considered. One of the most important advantages of using the Markov chain to determine the limit equilibrium point is to find this point in the shortest time and with the least available calculations.

Software defined network is a new computer network architecture who separates controller and data layer in network devices such as switches and routers. Separation of the control plane and the data plane has many benefits, such as more programmability of the control plane, the possibility of network virtualization, reduction of operating costs, greater independence of network equipment manufacturers, and so on. By the emerge of software defined networks, a class of location problems, called controller placement problem, has attracted much more research attention. The task in the problem is to simultaneously find optimal number and location of controllers satisfying a set of routing and capacity constraints. In this paper, we suggest an effective solution method based on dynamic switches allocation. We, then compare our method to an existing standard mathematical programming solver on an extensive set of problem instances. It turns out that our suggested method is computationally much more effective and efficient over small to large instances.

Nowadays, the business environment has provided causes of emerging a high level of uncertainty and turbulent behavior in supply chains. In most cases, suppliers are considered as the main sources of external risks which provide causes of emerging wide levels of disruptions in supply chains; therefore, choosing the appropriate and also resilient suppliers can greatly reduce purchasing costs and delay times and also increase the ability to maintain business in the case of disruption, competitiveness of the company and satisfaction of customers. This study is aimed to identify and investigate the attributes for evaluating the suppliers’ resilience from the two aspects, the importance and effectiveness of choosing the resilient suppliers in Iran electronic industries. In this regard, screening, dematel, analytic network process and goal programming have been used that they were performed in the fuzzy environment due to the uncertainty of the nature of all researches. Results showed that some attributes including, human resource management, visibility, and financial strength are the most influential factors. In terms of importance, agility, adaptability, and vulnerability are also the most important factors. At the end, while presenting a case study of the industry and applying goal programming, the ability of the proposed combined model in solving the real-world problems is shown.

Analysis and modelling the projects interdependency has become a vital and inevitable issue in project portfolio management. Present study focused on investment risks interdependency modelling in a project portfolio. Risk in projects as an integral element reduces the accuracy of the goals and the efficiency of the projects. Identifying, analyzing, prioritizing and having plans to deal with these potential negative elements play a significant role in the success of the projects. In this paper, using Delphi Method and fuzzy cognitive mapping (FCM) as a powerful tool in the field of soft knowledge domains occasionally soft operation research, the direct and indirect causality between the risks affecting the return on investment in the development of refineries in Iran are identified and explained. Thus, using a hybrid qualitative and methodological approach, cognitive processes and all the outcomes are based on the system of meaningfulness of the experts’ and professionals’ mental models in the field of refinery. Identified risks generally fall into four spheres of technology, marketing, finance and legal-political. Finally, using soft modeling, a network structure is presented as a potential negative factors affecting the return on investment, which leads to clarifying the dependencies and impact severity of forward and backward chaining. Furthermore, centrality criteria are used as a tool for static analyzing of created fuzzy cognitive map in order to interpret and give the meaning to the causal relationships between nodes.