نیکبخش جوادیان

Every year, the crisis in human societies is growing up in type, number and severity, so today crisis management is considered an important topic for research and research in all countries. In this study, a proposed multi-objective mathematical model under uncertainty conditions. The model seeks to find the optimal facility location and allocation of goods between the facility and the allocation of injured to hospitals also Looking for an optimal route to bring human resources to damaged areas to achieve goals such as reducing costs, distributing goods and fair medical assistance between areas, and reducing the time that aid troops arrive in damaged areas. The existing model focuses on the severity of incident uncertainty and this uncertainty in the severity of the accident, which causes uncertainty about the amount of demand for goods and manpower, and the amount of damage and injuries is based on a scenario-based method based approach Robust optimization in the model and because of the multi-purpose of the model, with the help of one of the single-purpose methods, the model is made single-purpose and finally, the model in this study was solved in a case study to prove its accuracy and effectiveness was investigated.

In the present competitive world, the necessity of minimizing costs and production time and increasing the productivity in manufacturing systems are more and more felt. Because when production costs are reduced, the final price of product is reduced too and when the production time is reduced, afterward the response time to customers order is reduced too. This paper presents a bi-objective mathematical model of multi period cell formation problem base on grouping efficacy in dynamic environment with the flexibility in operator assignment. The advantages of the proposed model are as follows: considering multi period planning horizon, dynamic system reconfiguration, duplicate machine, machine capacity, available time of operators and operator assignment. The aims of the proposed model are to maximize the total value of grouping efficacy (TVGE) and minimize the total costs (TC) include purchasing new machines cost, machine overhead cost, machine processing and reconfiguration costs, hiring, firing and salary costs. Computational results are presented by solving some numerical examples with improved e-constraint method to validate and verify the proposed model.

Since hazardous material transportation has been dramatically increased in terms of quantity, their incident impacts are getting to be known as a serious concern. Therefore, transport risk is usually considered as a main factor in hazardous material transportation and management. In this paper, a bi-objective mathematical model is developed for solving the fuel distribution problem, in which routing and location problems are solved simultaneously. While the problem is formulated as a mix-integer programming (MIP) model, distribution centers are considered as candidates, in which its main aims are to select the best set of establishing centers and find the best routes for carrying fuels from selected distribution centers to gas stations. The proposed model is eventually validated using the experimental data. Finally, the associated results are analyzed and the conclusion is provided.

The use of System Dynamics Modeling in Supply Chain Management has only recently re-emerged after a lengthy slack period. the propose of this thesis is to use knowledge and techniques in implementation based on recent research. At first we have given an overview of supply chain management and system dynamics and then presented a taxonomy of research and development in System Dynamics Modeling in supply chain management. In this research we have focused on a supply chain as a case study Which produce and distribute healthy products and its main company is darugar. we used System Dynamics techniques to know effective variables in our supply chain and understand how to improve its performance. we started simulation model design by explaining dynamic hypothesis and continued by creating casual loops, stock & flow diagrams and mathematical formulation. our model was tested by famous dynamics and statistical techniques and then we started to investigate causes of supply chain’s behavior by sensitivity analyses. when we understood the main factors and their interactions completely we started to suggest three policies due to supply chain indexes to improve its performance. the policies are missed sale reduction, inventory reduction and correct information receive which all causes improvement in introduced indexes in our research. what we achieved of this research was our ability of predicting results before any changes in parameters, relationships or structure of supply chain and it is so important due to its high degree of complicity.