In this paper an uncertain multi objective closed-loop supply chain is developed. The first objective function is maximizing the total profit. The second objective function is minimizing the use of row materials. In the other word, the second objective function is maximizing the amount of remanufacturing and recycling. Genetic algorithm is used for optimization; and for finding the pareto optimal line, Epsilon-Constraint method is used. Finally a numerical example is solved with proposed approach and performance of the model is evaluated in different sizes. The results show that this approach is effective and useful for managerial decisions.

This article aims to research the multi-leader-follower games with Fuzzy Constraint mappings(MLFFGs), in which the feasible strategy mappings of the leaders are Fuzzy mappings. By using the Fan-Glicksberg fixed point theorem, an existence theorem of equilibria for the MLFFGs under some conditions is obtained. Furthermore, with the assumption of finite rationality, we prove the stable results on the generalized well-posedness, the generalized Tykhonov well-posedness, and the generalized Hadamard well-posedness of Fuzzy multi-leader-follower games.

Landing impact and runway unevenness have proximate consequence on performance of landing gear system and conduce to discomfort of passengers and reduction of the pilot’ s capability to control aircraft. Finally, vibrations caused by them result in structure fatigue. Fuzzy logic controller is used frequently in different applications because of simplicity in design and implementation. In the present paper, this control approach is performed by minimum error criteria procedure and bees algorithm as the optimization technique for the model of semi-active suspension system that chooses damping performance of shock absorber at touchdown to be the purpose of control on landing gear and its efficiency is evaluated with the competence of passive control. Results of numerical simulation by matlab/simulink software indicate that the force induced to body and the vertical vibration of fuselage have important improvement )60% and 50%( for Fuzzy intelligent method optimized by bees algorithm compared to passive approach which lead to increase in quality of landing, easiness of passengers and structure’ s fatigue life in various operation conditions.

Due to the importance of vehicle routing for delivering a large number of orders with different restrictions in the world, various optimization methods have been studied in past researches. In this article, a number of researches of recent years have been discussed, then the proposed model is described in 3 phases with the penalty index. This model has the ability to assign orders, route vehicles and determine the number of active vehicles dynamically with the aim of minimizing the total cost of distribution. By examining valid metaheuristic models and using their strengths and weaknesses, and considering multiple limitations, a new model of "dynamic 3-phase optimization" has been designed. The main application of the proposed model is for vehicle routing problems with capacity Constraints of fleet number and capacity Constraints (maximum and minimum number of orders). Finally, with simulation, the outputs of the model have been analyzed in different conditions . Although the limitation of maximum and minimum capacity is added to the problem, by dynamically considering the number of vehicles and using star clustering (initiative of this research), three social, environmental and economic dimensions were improved. The time for orders to reach customers decreased by 19.3%, fuel consumption and air pollution by 14.9%, and logistics costs by 8.7%. To calculate the final value of system stability, a unique 3D Fuzzy model has been used. With the sensitivity analysis, we came to the conclusion that the 3-phase dynamic optimization model has led to a 14.58% improvement in system stability.

This paper presents a Fuzzy-neural approach for Constraint satisfaction of a generalized job shop scheduling problem (GJSSP) with Fuzzy process time. This paper is an extension of recently developed research carried out in the literature. However, we assume that the process time is uncertain. Due to NP-hard nature of the problem, there is a need of using a metaheuristic method.The first step of any metaheuristic method is to generate initial solutions. Thus, the proposed Fuzzy neural approach can adaptively adjust its weights of connections based on the sequence, resource, and uncertain process time Constraints of the GJSSP during its processing. Simulations have shown that the proposed Fuzzy-neural approach is efficient with respect to the capability of accessing to feasible space and the solution speed.

Constrain is the condition of driven by necessity. The principle of Constraint determines the duties of the person constrained. In jurisprudence, it includes a range of activities from cleanness to blood compensation. However, jurisprudents have discussed it mainly with regard to those that can be eaten and drunk, and presented three different interpretations: fear of losing one"s life; fear in general, including fear of losing one"s life, or one"s limb, etc.; and fear of things not related to oneself but to others. The roots of Constraint are compulsion, precautionary concealment, loss and necessity. The present article deals with a kind of Constraint whose source is necessiy. The Qur"an has explicitly excused the person constrained from duties provided that the oppressor shows no inclination to sin. Tradition says that "there is so unlawful act that God Almighty has not made it permissible under Constraint." The intellect also knows it permissible to give up necessary duties and to do the unlawful acts under Constraint. Finally, the writer presents the conditions under which the application of the principle of constrain is made permissible.