Penalty Function Approach in Heuristic Algorithms for Constrained Redundancy Reliability Optimization

Agarwal, Mukesh; Gupta, Ruby

doi:10.1109/tr.2005.853285

Cited by 51 publications

(22 citation statements)

References 15 publications

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“…Therefore, we employed the penalty function method [21] to transform the problem into an unconstrained optimization problem. The fitness function F is designed as follows: (15) where, N p is the number of constraints that are not satisfied.…”

Section: Solution Of Double-q Planning For Disribution Network Amentioning

confidence: 99%

A Practical Large-Scale Distribution Network Planning Model Based on Elite Ant-Q

et al. 2020

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In order to effectively apply the detailed geographic and load information provided by digital technology, this paper proposes a practical double-Q planning model for large-scale medium voltage distribution network. Meanwhile, a coding method and an elite Ant-Q algorithm(EAQ) suitable for solving the model in this paper are proposed. Based on the basic characteristics of the medium voltage distribution network, the components in the distribution network are abstracted into nodes and branches in the graph theory. A variety of practical issue, such as cost parameters (investments, maintenance, reliability) and technical constraints (feeder capacity constraints, number constraints of substation feeder), as well as road network constraints and connection mode constraints are taken into consideration. In addition, the storage of road network matrix information, reliability evaluation algorithm and model solving algorithm are suitable for large-scale distribution network. Finally, the proposed model and algorithm are applied to a business area to be planned in Guangzhou, which verifies the effectiveness of the proposed model and algorithm. INDEX TERMS Large-scale distribution network planning, double-Q planning, EAQ, sequence coding, shortest path method, closed loop design. NOMENCLATURE INDICES TAO YU (Member, IEEE) received the B.Eng. degree in electrical power system from Zhejiang University, Hangzhou, China, in 1996, the M.Eng. degree in hydroelectric engineering from

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Section: Solution Of Double-q Planning For Disribution Network Amentioning

confidence: 99%

A Practical Large-Scale Distribution Network Planning Model Based on Elite Ant-Q

et al. 2020

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“…A huge number of techniques, including heuristic and metaheuristic, have been developed for solving redundancy allocation problems for complex systems in the literature. 16,[18][19][20][21][22][23][24][25][26][27][28][29][30] Shi 19 proposed a heuristic algorithm to solve problems of redundancy allocation based on minimal path sets. Here, the feasible solutions obtained in successive iterations are in 1-neighborhood or 2-neighborhoods of each other.…”

Section: Introductionmentioning

confidence: 99%

Minimal path set importance in complex systems

Aggarwal

2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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To find the best mode for system design in reliability optimization, risk engineers around the world use the importance measure as a basic tool. This paper introduces a new importance measure taking into account minimal path sets of the system. It helps to optimize the system designs that occur in many situations. For instance, this importance measure can be used (a) in identifying important components of any complex system and (b) solving constrained redundancy optimization problems. This is illustrated by providing two heuristic algorithms. In the first algorithm, this measure is used to find important components of any complex system ensuring improved system reliability. The second algorithm is used to solve a constrained redundancy optimization problem for any general coherent system giving (near) optimal solutions in 1-neighborhood. The results show that the new importance measure is easily applicable, unlike the classical ones. Hence, it serves as a very useful tool in measuring the important component(s) and solving constrained redundancy optimization problems of complex systems. Thus, it can be considered as a good alternative to the existing importance measures.

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“…Over the past decades, several deterministic methods have been used to solve the RRAP, such as the heuristic methods [9][10][11], the branch and bound method [12,13], the integer programming [14] and the dynamic programming method [15,16]. However, these methods have shown some weaknesses.…”

Section: Introductionmentioning

confidence: 99%

A swarm intelligence-based approach for reliability–redundancy allocation problems

Guedria

Hassine

2019

J Braz. Soc. Mech. Sci. Eng.

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This paper presents a new algorithm belonging to the class of swarm intelligence methods, called the adaptive simplified PSO (ASPSO)-based algorithm, for solving reliability-redundancy allocation problems. In this constrained nonlinear mixed-integer problem, both the number of redundant components and their reliability in each subsystem are to be decided simultaneously so as to maximize the reliability of the system. The proposed ASPSO operates with a new updating model to adjust the position of particles, without dealing with velocity. In addition, a randomization technique, based on the dispersion of particle bests through the search space, is used to speed up the convergence of the proposed approach and prevent it from being trapped within the local optimum. Moreover, to control the balance between exploration and exploitation, during the search process, two adaptive functions are utilized. The simulation results of four different benchmarks for the reliabilityredundancy allocation problem are reported and compared. Accordingly, the solutions given by the new presented approach are all superior to those best known solutions provided by several methods in the literature.

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Penalty Function Approach in Heuristic Algorithms for Constrained Redundancy Reliability Optimization

Cited by 51 publications

References 15 publications

A Practical Large-Scale Distribution Network Planning Model Based on Elite Ant-Q

A Practical Large-Scale Distribution Network Planning Model Based on Elite Ant-Q

Minimal path set importance in complex systems

A swarm intelligence-based approach for reliability–redundancy allocation problems

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