نشریه پژوهش های نوین در تصمیم گیری
سال سوم شماره 1 (بهار 1397)

Needs of affected people for relief commodities in the natural disasters often make crisis worse. Therefore location of distribution of depots and setup these depots wherever accelerate fast distribution have a special importance. In this paper a location-allocation model of distribution facilities with the objective of minimizing the costs has been proposed. So that this model under uncertainty allocates the established depots to affected areas under different scenarios considering dynamic demand in which over the first 72 hours after the beginning of the crisis. Also two kinds of reliable and unreliable depots and backup depots with the possibility of damage to facilities and routs has been considered to increase the reliability. The proposed model has been applied on a case study the earthquake in Tehran city. Then we have solved the problem for a different number of facilities and performed a sensitivity analysis and validation process. Also the demand for relief has been forecasted for the year 1398 with the ARMA method and the results have been reported. Computational results show that location of distribution depots and allocation of the areas according to the proposed modelcan improve the aid and help managers to manage the crisis.

Passenger transferring between origins to destinations, regarding the matter of the variety of services are the main goal in a public transportation (air and ground systems). So, considering the different types of vehicles and increasing different levels of services are the essential issues in hierarchical hub location problems. As well as the effect of disruption (Deliberately and unintentionally), changing the scope of the connectivity in a distribution systems, locations, re–allocations and designing the sustainable network in the presence of disruption are the problems which are less reviewed in a hierarchical hub location field. In this paper a linear model used for designing a sustainable capacitated hierarchical hub location problems considering multi modes of transportation based on two scenarios, with or without any disruption. This model has been solved with GAMS 23.4.3 optimization software and Monte Carlo simulation method (MATLAB R2016a). Based on the results of the network without any disruption, the disruption probability obtained to be used in a network under disruption. The results show that, the model and the proposed solution method, can satisfy the demands in the presence of disruption, changing the location of non–central hub nodes and the re–allocation in each levels of hierarchy. Increasing the discount factors, disruptions and the number of non-central hub nodes increases the total costs of the hierarchical hub network. Also increasing the levels of services, considering the different paths and vehicles can expand the decision making ability in a network.

Facility location problem is one of the most important and useful topics in the field of decision-making. Cost reduction is always one of the main criteria in these problems. Since environmental concerns increment in recent years, harmful gas emissions and environmental pollution is regarded as other affective criteria in locating of facilities and also allocating them to customers. In this paper, a capacitated bi-objective facility location problem with multi-source and multi-product is studied. In this problem, financial costs and gas emissions are considered simultaneously. First the mathematical model is presented, and then a robustness analysis using Mont Carlo simulation method is applied for solving it. Through using this method it is possible to determine stability level of Pareto optimal solutions to make better decisions for establishing facilities and allocating customers to them. Finally, the computational results are presented.

The quantification of customer profitability and the retaining the profitable customers are the core of the customer relationship management activities and a critical part of growing a successful business. This research aims to provide a framework for measuring and evaluating customer profitability, categorizing them based on their value to the business and ranking them according to priorities of customer retention in the business. We implement a customer profitability analysis using time driven activity-based costing and the k-Means algorithm for clustering customers based on the modified RFM method. Finally, in order to quantify the customer behavior and ranking them, we map customer clusters into four conceptual categories. This research is a case study of the Charcoal Burger Restaurant Franchise in the Zafar Street Branch from Early December 2014 until the end of May 2015. Customer’s clusters include of today's loyal customers, customers of competitors, loyal for tomorrow and ready to offer competitors.

Sustainable growth of share value of a company, regardless of financial flow and integration of financial decisions with other physical decisions, is not reachable. Value based supply chain management, attempts to make it possible through managing working capital, assets and debts. Decisions regarding assets management and financing has always been though decisions every company face. Such decisions, are affected by financial ratios which has not been considered in any optimization models. In this paper a mixed integer programming is presented to integrate financial and physical decisions in a multi echelon, multi period and multi commodity supply chain in order to maximize economic value added, as a most prevalent value metric. Financing through short term borrowing considering fulfillment of financial ratios as well as option of credit buy and sell along with pre sell and pre buy are the most important contributions. Problems with different sizes are solved in order to approve effectiveness of the proposed model. The effect of financial ratios variation and various buy and sell options on supply chain value are analyzed afterward.

Basic probability assignment or mass function is an important tool in Dempster-Shafer theory. Based on this function, belief and plausibility functions are used to present insufficient, inconsistencies or conflict information. Generally, the information source is based on expert’s opinions when the deterministic probability of any proposition may not be obtained. In this paper, a new method for solving multi-criteria decision-making is proposed based on belief functions. Three main elements are considered in the definition of the belief functions are: (1) the degree of the true belief or belief function, (2) the degree of the false belief or non-belief function (3) the degree of uncertainty for each alternative among alternatives. In the proposed method, the amount of different distance between an alternative and the ideal alternative can be measured based on the minimum and maximum operators. It may help to utilize the belief measure between the ideal alternative and each alternative to rank the alternatives with respect to measure the value and then select the desirable one. Furthermore, in the proposed method, the weighted criteria and weighted belief function are considered in the decision-making process. Finally, two illustrative examples are given to demonstrate its application effectiveness.

Minimization of costs and maximization of product quality are key factors for success in a supply chain network (SCN).The SCN is considered four echelons: suppliers, middle assemblers, final assembler and retailers that supply a single type product consists of four components. In this paper in addition to the supplier selection, the assemblers and warehouses are selected. The assembly process of the products such as automobile, tractor, consist of multiple stage, therefore in this paper, the assemblers are divided in two groups: multiple middle assemblers (which assemble the component of the product), a final assembler (assembles the final product). In this paper an integrated approach for middle assemblers selection based on multi attribute decision making (MADM) and suppliers selection based on multi objective decision making (MODM) is proposed. First the weight of the attributes (cost, quality, delivered time and warranty) is determined by ENTROPY method and then the middle assemblers are selected by TOPSIS method. The model consists of two minimization of costs and maximization of quality which is solved by CHEBYSHEV goal programming to select suppliers. Application of proposed method is shown by numerical example and optimal solutions have been compared considering one objective and two objectives.

Nowadays, organizations are encountered to increasing complexity and uncertainty in their internal and external environment. A well-designed organizational structure is a cornerstone of achieving an organization’s goals while suiting the environmental challenges. Design models for organization structure must be in a way to consider the inherent complexity of the environment as well as the complexity of stakeholders’ relationships. Viable System Model (VSM) which is rooted in Organizational Cybernetics, is capable of considering the external and internal complexities of organizations. This approach is an outline for diagnosing and designing organizational structure. The fundamental idea of VSM is the existence of specific systems, and their relations in an organization. These can lead the organization toward viability and survivability. This study employed VSM for diagnosing the organizational structure of Iranian Construction Engineering Organization based on three steps methodology which includes system identification, system diagnosis, and checking information flows, communication channels and frequent faults. Applying proposed methodology shown that, a set of systems, information flows, and communication channels have deficiencies in the organization, which needs to be amended in order to achieve viability and the ability to cope with the challenges.

In Iran the rate of natural disasters, especially the earthquake, is very high, hence the humanitarian supply chain management before, during and after the disaster occurrence is very important. In other hand emergency medical centers are main part of this chain. Emergency medical centers with timely treatment of injuries reduced the irreversible damage of disaster. Therefore, the location of these centers has a major role in reducing the response time to affected people and the locating of these centers is very important. The main objective of this study is to determine the location of emergency medical centers in order to maximize the demand coverage and reduce the rescue time in a humanitarian supply chain. In order to solve the emergency medical centers location problem a mathematical model was presented, considering some conditions for the problem and sought to find the optimal locations for the establishment of these centers. To solve this problem, an innovative algorithm was presented in which two meta-heuristic algorithms were used. Then, 16 scenarios were solved by using the proposed algorithm. Due to the accuracy of the obtained responses and the high speed of the convergence of the proposed algorithm, it can be used in large and complex problems that cannot reach the exact answer in a reasonable time.

Operation research and system architecture/architecting are two fields to tackle complexity. Both of them are widely used in various discipline. However, architecture/architecting is most dominant than OR to tackle complex problems. Survey on system architecture/architecting literature, show the lack of process of creating architecture. In this paper we want to compare fundamental philosophy of both in methodology level to show usefulness of Operation research approaches to create theory for system architecting/architecture. According to this, using categorical logic, different Operation research approaches- Hard Operation research, soft Operation research and critical Operation research - except Postmodern Operation research can be useful tools to system architecture/architecting. So in first step categorical propositions of system architecture/architecting and Operation research paradigms was extracted and then based on categorical logic they were compared. In addition, LISP programming language was used to standardize the writing. Finally, a summary of the results was presented in the form of a conceptual hierarchies of architecting and Operation research adapted from the conceptual hierarchies introduced by Paul Thagard. This conceptual hierarchies is representation of the relation between Operation research approaches and system architecting.

Designing supply chain network system is one of the basic issues in supply chain management. In supply chain, financial flows exist like physical flows. The purpose of this study is to design a four level supply chain network considering holistic and systems thinking, which was conducted in three stages. The first stage, deals with tactical and strategic level of decision making –unlike previous studies- has considered both financial and operational considerations and has integrated the financial and operational dimensions by mathematical modeling. In the second stage, the mathematical model was optimized according to the company’s value and besides that, this new approach has been evaluated and compared with traditional approaches that only focus on minimizing the loss or maximizing the profit. In the third stage the value of the company and change in its equity, as two objectives of the companies are optimized simultaneously and compromised using fuzzy goal programming. Sensitivity analysis on main parameters was conducted. GAMS and CPLEX solver were used as software for mathematical modeling. Results indicated on the importance role of financial approach and integration of financial and operational approach in chain purposes and obtaining sustainable competitive advantage. In addition, results clearly revealed the deficiencies of traditional approaches that disregard financial view and holistic and integrated approach to the supply chain.

The implementation of ERP systems in organizations involves the use of financial, human and knowledgeable capital;therefore, it is very important to analyze the effective criteria and factors in choosing this system.The purpose of this study is to explain the structural relationships between the mentioned factors in active companies in automotive industry.The data for this research was collected with a survey of experts with at least 10 years of experience in consulting and management in the field of information systems and implementation of systems.Using the DANP method, the internal relations between the criteria and the critical importance of each of them were analyzed. In the following, the ISM method was used to structure the criteria and present a systematic model for decision makers.The results of this research provide a more accurate understanding of the key criteria for choosing the appropriate ERP system. So this recognition can pave the way for the implementation and control of the system for automotive executives.