A Multiobjective Genetic Algorithm for Solving Reliability Optimization Problem of the Complex System
نویسندگان
چکیده
In this paper, we propose a multiobjective Genetic Algorithm (mo-GA) for solving a multiobjective reliability optimization problem. In order to obtain high efficiency of searching non-dominated solutions, we combine the Improved Saving Pareto solutions Strategy (ISPS) and the adoptive Local Search (LS) with the multiobjective Genetic Algorithm. Through some numerical experiments, we evaluate the reliability optimization problem of the complex system, and show effectiveness of the multiobjective Genetic Algorithm.
منابع مشابه
Multiobjective Imperialist Competitive Evolutionary Algorithm for Solving Nonlinear Constrained Programming Problems
Nonlinear constrained programing problem (NCPP) has been arisen in diverse range of sciences such as portfolio, economic management etc.. In this paper, a multiobjective imperialist competitive evolutionary algorithm for solving NCPP is proposed. Firstly, we transform the NCPP into a biobjective optimization problem. Secondly, in order to improve the diversity of evolution country swarm, and he...
متن کاملSolving Redundancy Allocation Problem with Repairable Components Using Genetic Algorithm and Simulation Method
Reliability optimization problem has a wide application in engineering area. One of the most important problems in reliability is redundancy allocation problem (RAP). In this research, we worked on a RAP with repairable components and k-out-of-n sub-systems structure. The objective function was to maximize system reliability under cost and weight constraints. The aim was determining optimal com...
متن کاملSolving a Redundancy Allocation Problem by a Hybrid Multi-objective Imperialist Competitive Algorithm
A redundancy allocation problem (RAP) is a well-known NP-hard problem that involves the selection of elements and redundancy levels to maximize the system reliability under various system-level constraints. In many practical design situations, reliability apportionment is complicated because of the presence of several conflicting objectives that cannot be combined into a single-objective functi...
متن کاملSolving a New Multi-objective Inventory-Routing Problem by a Non-dominated Sorting Genetic Algorithm
This paper considers a multi-period, multi-product inventory-routing problem in a two-level supply chain consisting of a distributor and a set of customers. This problem is modeled with the aim of minimizing bi-objectives, namely the total system cost (including startup, distribution and maintenance costs) and risk-based transportation. Products are delivered to customers by some heterogeneous ...
متن کاملSolving a Joint Availability-Redundancy Optimization Model with Multi-State Components with Meta-Heuristic
This paper has been worked on a RAP with multi-state components and the performance rate of each component working state may increase by spending technical and organizational activities costs. Whereas RAP belongs to Np-Hard problems, we used Genetic algorithm (GA) and simulated annealing (SA) and for solving the presented problem and calculating system reliability universal generating function ...
متن کامل