SEYYED ALI Mirnezhad; Parham Azimi; Ahmad Yousefi Hanoomarvar
Abstract
In the present study, the redundancy allocation problem (RAP) of series-parallel system has been investigated to maximize the system's availability. To achieve the research objective, budget, weight and volume constraints, and the maximum and minimum number of elements assigned to each subsystem have ...
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In the present study, the redundancy allocation problem (RAP) of series-parallel system has been investigated to maximize the system's availability. To achieve the research objective, budget, weight and volume constraints, and the maximum and minimum number of elements assigned to each subsystem have been considered. The main innovation of this research is to consider the failure and repair rates of components with non-exponential distribution function in the process of optimization. Taking into account failure and repair rate via non-exponential distribution function makes it impossible to calculate accessibility using mathematical relations. Therefore, the present study has used simulation method to calculate system availability. Since the simulation has no optimization capability On the other hand, in the redundancy allocation problem, it is necessary to evaluate the system availability recurrently in order to find the optimal solution. Further, due to the high degree of difficulty of developed mathematical function, the genetic metaheuristic algorithm was used to solve it. Finally, the efficiency of the genetic algorithm was measured against particle swarm algorithm and simulated annealing algorithm. To compare fairly, the parameters affecting the algorithms are adjusted using the Taguchi method and the algorithms are in their best practice. The computational results prove the high ability of the genetic algorithm in optimizing the concerned problem.
Neda Manavizadeh; soroush aghamohamadi-bosjin; Parisa Karimi-Ashtiani
Abstract
This paper proposes a bi-objective model for the waste collection problem and considers the location, routing and inventory of the system simultaneously. Considering the reverse flow of the system is another feature of the current study. In the proposed model, the total costs of the system are minimized. ...
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This paper proposes a bi-objective model for the waste collection problem and considers the location, routing and inventory of the system simultaneously. Considering the reverse flow of the system is another feature of the current study. In the proposed model, the total costs of the system are minimized. In addition, the related risks of opening new centers and transportaion are included as the second objective function of the problem. Considering the delivery time and cpacity of vehicels constraints, are the other features of the model. Due to the NP-hardness of the model, two metaheuristic algorithms namely a non dominated sort ordering genetic algorithm (NSGA-II) and a multi objective particle swarm optimization algorithm (MOPSO) are applied to solve the problem. According to the results, NSGA-II is able to reach better answers in all the propsed metrics. According to sesitivity analysis, foreign transportation fleets make a great impact on the costs of the system.
