multi-objective planning

Supplier selection is one of the most critical problems in the supply chain management that helps firms to evaluate and select appropriate suppliers. Different conflicting objectives could be considered in these kinds of problems. Most important objectives are: minimizing the cost, maximizing the quality, and maximizing the reliability. In this paper the set of suppliers are considered as a system and they are selected so that maximizing the reliability of the selected set and maximizing the quality of the received products, and also minimizing the purchasing cost. On the other hand, in practice exact data are not accessible, therefore, fuzzy theory is utilized to evaluate the suppliers. In addition, suppliers usually use discount mechanism to attract more buyers and to achieve more profits. In this paper supplier selection problem is modeled considering all unit discount. Additionally, satisfaction of the demand depends on the risk attitude of the buyer. The satisfaction of the demand is considered as a fuzzy-probabilistic constraint. Finally, a numerical example is solved based on different risk attitudes of the buyer and related results are reported.

Proper management and optimal allocation of financial resources will increase gross national product and growth, create jobs and increase public welfare. The purpose of this study is to present an investment strategy that has tried to pave the way for the development of the investing company in the financial markets. Therefore, the forthcoming research can be considered as applied in terms of purpose. Also, considering that in the present research, mathematical modeling, modeling, artificial intelligence, etc. are used and the optimization of the investor company's portfolio is evaluated with the proposed model, so it is a quantitative and descriptive research. This study evaluated the performance of the proposed model in three modes: prudent, moderate and risky investor company. The results showed that for all three cases, the proposed strategy performs significantly better than the market index and other previous strategies. At the end of the investment period, the risky portfolio was more valuable than other portfolios. On the other hand, a prudent portfolio has achieved a more stable and stable return. These results revealed that the proposed fuzzy programming is able to reflect the characteristics and desires of the investor company in the portfolio composition.

The development of a variety of public transportation systems that cover different areas, has made it difficult for passengers and users to choose the type of transportation system and appropriate route between two specified departures. In large cities such as Tehran, a network of public transportation systems, called multi-modal systems, consist of stations as nodes and public transport vehicles intermediate between the two consecutive stations as arcs, is formed. Travelers are looking continuously for a way to find the optimal route in complex multi-modal transportation networks to reach their desired destination with minimal cost and confusion. In this paper, two linear and nonlinear multi-objective programming models with three objective functions have been developed for routing in multi-modal transport systems. The objectives of the proposed model are to minimize the cost, travel time and the number of vehicle types. By examining the validation of models by test issues, two exact and meta-heuristic algorithms (ant colony algorithm) have been developed to solve the proposed model. The results of the evaluation of the performance of the solving methods indicate that problem solving by exact method for networks with more than 15 nodes are non-operating, while the meta-heuristic algorithm provides the same problems with same precision in the exact method but with logical time.

Operations research is a commonly used method in many subjects nowadays. One applicable domain of operation research is the problem of facility layout and location. In this paper، a new mathematical programing model is developed for an optimal facility location and assignment. The model includes two objective functions. The first one minimizes the total material handling and fixed costs of facility location. Because of the importance of energy and the main role of fossil fuel in transportation، the second objective function، minimizes the total cost of fuel consumption. To consider the real condition in the proposed model، the cost of fuel، is considered to increase stepwise gradually. In the proposed model the coefficients of objective function are considered to be probabilistic and some of constraints to be fuzzy variables. Using a new approach، this model can be changed to a robust model. To prove the applicability of the model، it is examined for a real condition of facility location.