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Increasing trend in the number of vehicles and consequently intensifying the traffic volume, traffic lights optimum timing plays a vital role in congestion mitigation in the critical intersections of urban areas. This paper gives an insight into traffic light timing using simulation modeling methods. In fact, this study aims at minimizing the average time that entities (vehicles) spend in the system (intersection). First, real data including vehicles arrive and leave times, and the time spent waiting at a red light etc. is collected through monitoring an intersection in downtown Urmia, Iran. Then, a simulation model is developed using Arena Simulation Software. The most important feature of the proposed model is the replacement a four-stroke traffic light with the current three-stroke one. After model validation, several alternatives are considered for traffic light timing and the one which resulted the minimum average time spent in the system is selected. According to the simulation results, the four-stroke traffic light yielded a better performance compared to the three-stroke one.
This paper presents a novel and versatile method for finding 2-D tensegrity structures form finding. Using this method, different possibilities for the geometry of 2-D tensegrity structures can be found with little information about the structure. As opposed to most existing procedures this method only needs the number of each member prototype, the number of tensegrity nodes and connectivity at each node to be known. The form finding is done by minimizing objective function, which considers the rank deficiencies of the geometry, the prestress coefficients and the semi-positive definite condition of the stiffness matrix. Genetic algorithm as the global search is taken into account first for generating the connectivity matrix, initial prestress coefficients and also minimizing the objective function. Several numerical examples are given to demonstrate the competence and robustness of the current study in searching new different possibility self-equilibrium configuration of tensegrity structures.
Abstract. In recent decades, many researchers have studied the cellular manufacturing system with consideration of various issues such as scheduling, production planning, layout, reliability, etc. However, limited research papers have investigated this problem in an uncertain environment. The present paper addresses a stochastic problem in cellular manufacturing systems considering simultaneous multiple routings and subcontracting. In the developed problem, each part can be simultaneously produced in multiple processing routes. It is also assumed that the unsatis ed part demands as a result of limited machine capacity or high manufacturing cost could be outsourced. A two-stage stochastic programming approach is employed to take the uncertainty into consideration and to formulate the problem. The objective function is to minimize the summation of production, subcontracting, material handling, and machine idleness costs. A sample average approximation method is applied as a solution method. Also, for further illustration of the problem, a numerical example is solved and sensitivity analyses are conducted. Finally, through some numerical examples extracted from related literature, the advantages of constructing a stochastic optimization model for the problem are demonstrated.
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