In some countries, regional authorities may attempt to rebalance the alLocation of National facilities in benefit of their own region which, in turn, may cause disturbances in the central government’s decision-making proces. Regarding the hierarchical nature of these types of decisions, classical optimization models are not effective in decision-making and the use of multi-level Programming can increase the efficiency of planning. Our paper aims to address the issue of a bi-level Programming model to conduct the Location analysis of Emergency Warehouses. A three-echelon relief supply chain is considered in which the relief network involves National and regional Warehouses and demand cities. The upper-level model decides on the Location of National Warehouses, allocating them to regional Warehouses. The lower-level model determines the Location of regional Warehouses and allocates them to demand points. The structure of both levels is based on the median Location-alLocation problem. Three solution approaches are presented based on the full enumeration and two types of nested Evolutionarymethods (genetic and heuristic local search Algorithms). For the model to be used in Iran, the efficiency of Algorithms is analyzed for two sizes of problems. The obtained results show the proper functioning of the solution approaches.

IntroductionSince locating distribution Warehouses is not easy to do, using a decision support system will help increase the effectiveness of decisions in this area. Accordingly, in this study, the aim is to use a model in addition to introducing the most suitable Location for the construction of the central Warehouse, to calculate the desirability of the desired Location using multi-objective linear planning to determine potential and proposed Locations. To what extent can they be a good place to build a central Warehouse?Literature ReviewProper Location of distribution Warehouses are the main key to productivity, which can be used to achieve various goals of the organization, such as providing optimal services to customers and at the same time reducing distribution costs. Warehouse Location is related to the placement and orientation of a piece of land according to the Location of consumers and suppliers of the Warehouse, and it consists of determining the Location of the Warehouse in such a way that its goals are met. Determining possible Locations for Warehouses varies from organization to organization and from one situation to another. Decision making in this case requires careful planning and proper forecasting and some analysis. However, the scientific method of planning directs the existing experiences into an optimal plan.MethodologyPrevious researches that have been conducted in the field of Warehouse Location have used different decision making methods to design a decision support system and introduced the appropriate Location for building a Warehouse. Now, the question that is raised is whether the same decision-making methods of the past can be the criteria for choosing the Location of the central Warehouse, or whether a new method should be used to design the decision support system based on the importance of the studied problem? Based on this, in this research, the purpose of using a model is to introduce the most suitable place for the construction of a central Warehouse, it calculates the desirability of the desired Location using the proposed multi-objective linear Programming, to determine the potential and proposed Locations. To what extent can they be a suitable place to build a central Warehouse? Optimal methods for decision making have always been considered and used in many important industrial issues. In the present study, the cumulative utility of the star, which is one of the most important methods for calculating and extracting utility functions, has been used.ResultsAccording to the planning of the managers for the development of the factory for new products, the need to have a central Warehouse to store the goods and to choose the right place requires attention to this matter. Based on this, the managers of Foulad Company are trying to take an important step by choosing the right Location for the central Warehouse, in order to reduce costs and the level of good service to the nearby workshops, as well as to increase profits. In this research, due to the importance of choosing a Warehouse Location and the complexity of making such a decision, we have presented a decision support system based on a multi-objective linear Programming model, which is able to provide appropriate assistance by considering the minimum information from the researchers. Increase the effectiveness of decisions and help managers and researchers in the process of making optimal decisions.DiscussionAccording to the findings, it can be argued that by using the obtained results, it will create the possibility for companies to make decisions to optimize the support system in their company and with this, in addition to reducing Costs to increase their competitiveness.ConclusionOn the one hand, according to the results of multi-objective linear planning, he has calculated and presented the overall desirability of the reference options, which include potential and proposed options for building a central Warehouse Location. Also, on the other hand, it deals with the sensitivity analysis of options to help managers and researchers in the process of making a favorable and optimal decision. The results indicate that the Warehouse Location has the first rank with 84% desirability as the most desirable central Warehouse Location of Damghan Steel Company. Also, the important point of the obtained results is that none of the proposed options can be the most desirable place for other sectors in the future.

Choosing the proper Location for service centers can play an important role in reducing travel costs for users, desirable use of the land, and regulation of interactions among different facilities. When Location-AlLocation (L. A. ) problem of any new service centers is solved for multiple facilities independently, only the effects of existing land uses are taken into consideration, while the establishment of one facility, due to its impact on the surrounding space, may cause limitations for the establishment of other required facilities. By locating all the required centers simultaneously, better results can be obtained for the arrangement of the centers in an area. The main objective of this study is to solve the L. A. problem for several service centers with similar or dissimilar services in GIS environment simultaneously. For this purpose, the Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) Algorithm has been used to optimize the three objective functions including minimizing travel costs, maximizing the suitability of selected sites, and maximizing the compatibility among the new service centers. The results showed that by using this method, acceptable solutions for the arrangement of different service centers in the study area have been obtained according to the defined objectives. The comparison of the results with Non-Dominated Sorting Genetic Algorithm II (NSGA_II), as one of the most common optimization Algorithms, based on various criteria, showed that MOEA/D method has performed well in finding optimized answers so that none of the solutions of this method were dominated by the solutions of the NSGA_II, while the reverse was not true. Besides, from the point of view of the closeness of the answers to the ideal point, MOEA/D has generated better solutions (0. 16) and the covered time has been 25% of NSGA_ II method.

The importance of locating critical facilities in hierarchical service delivery systems and fortification them against intentional attacks is the main subject of many researches, which helps the stability of the service system during intentional attacks by making appropriate decisions on Location and fortification.‎ In this paper , for the first time , the problem of locating hierarchical facilities with regard to the fortification and interdiction operations in a tri-level Programming model between system designer , defender and attacker has been proposed.‎‎ The aim of the system designer at the first level is to minimize the Location cost and service distance between the demand points and two categories of facilities.‎ The defender's objective is to adopt appropriate fortification operations at the second level in order to minimize the distance between customers and the nearest facility to receive primary services and referrals for secondary services according to available Location resources.‎ Meanwhile, the attacker in the third level of the model, as a follower, seeks to make decisions to assign customers to two categories of facilities and interdiction operations in order to maximize the service system distances.‎ To solve the new problem, a hybrid metaheuristic method based on genetic Algorithm, simulated annealing Algorithm and CPLEX has been proposed, and by solving several numerical examples, the the analysis of the results and the relation between the model parameters and the goals of the hierarchical service system is investigated.

The facility Location problem is a strategic decision-making for a supply chain which determines the profitability and sustainability of its components. This paper deals with a scenario where two supply chains, consisting of a producer, a number of distribution centers and several retailers provided with similar products, compete to maintain their market shares by opening new distribution centers because of increasing demand. The competition problem is formulated as a non-linear integer bi-level mathematical model, where the upper level represents the decisions of the leader producer and the lower level administrates the decisions of the follower producer. It has been shown that even in small-scale problems, bi-level mathematical Programming problems are strongly NP-hard, so an adapted bi-level ant colony Algorithm with inter-level information sharing is developed to solve the problem. To evaluate the performance of the developed ant colony Algorithm, the upper bound of the competitive facility Location problem is determined by solving the upper-level problem as an integer linear Programming model without considering the follower’ s decision. Comparing the computational results of the developed ant colony Algorithm with those of the determined upper bounds shows the satisfactory capability of the proposed approach for solving even medium-and large-scale problems.

In this paper, with emphasis on scheduling of head of crews for coach trains, a crew scheduling problem is presented in a network form with task arcs. To solve the problem, a meta heuristic Algorithm based on grouping Evolutionary Algorithm is developed. The grouping Evolutionary Algorithm contains two search methods which generate offspring from a parent chromosome; one of these methods is based on a logic constraints heuristic Algorithm, and the other one is relied on branch and bound approach. Computational results showed that combining grouping Evolutionary Algorithm and branch and bound approach generates good solutions, and for the problems that we knew their optimal solutions accomplish optimal outcomes. It is also shown that the Algorithm provides goods results for large scale real world problems.

The armed forces of each country, must always be prepared to deal with the enemy's invasion. For this reason, they must maintain their combat readiness by conducting military exercises. Military exercises are the best military exercises to deal with war conditions. A military exercise is conducted in a specific process and with presence of various military units in a specific territorial area. The goal of military exercises is to achieve educational goals at high levels with the maximum presence of all types of military forces. In this research, the problem of locating military units in the ground of exercise and the problem of deployment and counter-deployment in format of bi-level mathematical program are discussed. In this research, the Regional Headquarters is considered as the first level (leader) and the participating units (brigades) in exercise as the second level (follower), regarding that more than one unit is participating in the exercise, we deal with a multi-follower problem. The results of modeling and solving the model showed that if the principles used in this paper were used, selecting the appropriate place to conduct and selecting the appropriate place for each participant in the resume was done more desirable and more scientifically. Also, deployment and counter-deployment of the military equipment and military forces will be done With better control and time management, and if necessary, outsourcing will take place. Therefore, the use of scientific solutions in logistics planning is recommended.