This paper aims to minimize the expected daily inspection cost of a k-out-of-n load-sharing system with identical components. We consider a hybrid mixed-redundancy strategy for the components’ utilization at the beginning of each inspection interval when failed components are replaced by standbys using an imperfect switch. The number of active components at the beginning of inspection intervals as well as the duration of inspection intervals are varying, and depend on the number of available components. The components are assumed identical with a constant failure rate, which implies the components’ distribution function is exponential. We optimize both the number of active components at the beginning of each interval and the duration of the inspection intervals to minimize the system’s expected daily cost (SEDC). The SEDC has four components: the system’s inspection cost, the components’ repair cost, the system’s repair cost, and the system’s downtime cost. A new heuristic algorithm is used to optimize the model. Due to the model’s complexity, a genetic algorithm is suggested for large-size problems. The results show the model decreases the SEDC by a maximum of 64.89% compared to other existing strategies with fixed inspection intervals. 

Condition-based optimization of non-identical inspection intervals for a k-out-of-n load sharing system with hybrid mixed redundancy strategy

P-graph-based multi-objective risk analysis and redundancy allocation in safety-critical energy systems

Graph Theory with Applications to Engineering and Computer ... This outstanding introductory treatment of graph theory and its applications has had a long life in the instruction of advanced undergraduates and graduate students in all areas that require knowledge of this subject. The first nine chapters constitute an excellent overall introduction, requiring only some knowledge of set theory and matrix algebra.

Graph theory with applications to engineering and computer science, by Narsingh Deo. Pp xvii, 478. 1974. SBN 0 13 363473 6 (Prentice-Hall)

An Effective Oriented Genetic Algorithm for solving redundancy allocation problem in multi-state power systems

In this paper, we will discuss some algorithms in order to better optimize the problems of redundancy allocation in multi-state systems. The goal is to find the optimal configuration of the system that maximizes the availability and minimizes the investment cost. The availability will be evaluated using the universal generating function. In first step, our contribution consists in improving the genetic algorithm. In a second step, in the framework of the Constraint Programming, we propose a new method of optimization based on the Forward Checking as solver. Finally, we used the top-k method in our choice that helps us to get the best k elements from all possible values with highest availability. In comparison with the chosen study, our methods yield better results that satisfy the constraints of the problem in a shorter time.

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Some Efficient Algorithms to Deal With Redundancy Allocation Problems

Renewable energy1 power has been playing an important role in power production due to both being environmentally clean and its successful integration into the power systems. The evaluation of reliability of electrical networks is of a great importance among various players in the field of energy. The competitiveness in integrating renewable energies for implementing power plants has grown regarding their productivity, environmental and economic impacts. Following our exhaustive literature review, several limitations need to be pointed out. The proposed metaheuristic seeks the optimal design of series-parallel power systems in which a multiple choice of generators, transformers and lines are allowed from a list of product available in the market. The main advantage of the approach is that different parameters can be allocated in electrical power systems. To allow fast reliability estimation, a universal generating function (UGF) method is applied. And to obtain an optimal topology with minimal cost and a maximal availability under the constraint of performance, we introduce the Effective Genetic Algorithm (EGA) which is a hybridization of the genetic algorithm (GA) with UGF. The experimentation results and discussion show the effectiveness of our algorithm.

An Effective Genetic Algorithm for Solving Series-Parallel Power System Problem

In real life, we always want to reach our goal in minimum effort, it should have a minimum constrained path. The path may be shortest route in practical, either physical or electronic medium, or the minimum costing path in term of resources. The idea is to represent the problem as a graph and finding a spanning tree with specific design criteria. Here, we have chosen a minimum degree spanning tree, which can be generated in real time with minimum turnaround time [11]. The solution approach, in general, is approximate. We have used a heuristic approach, namely hybrid modified genetic algorithm (HMGA), with motivated criteria of encoded data structures of graph. We compare the experimental result with the existing approximate algorithms and the results are very promising.

Amine Amarir

Papers

An Effective Oriented Genetic Algorithm for solving redundancy allocation problem in multi-state power systems

An Effective Genetic Algorithm for Solving Series-Parallel Power System Problem

Degree Constrained Spanning Tree Problem Solving using Hybrid Modified Genetic Algorithm