A Comparison for Optimal Allocation of a Reliability Algorithms Production System

The most important phase in many industrial power applications is the design problem. Usually the demand increases randomly with time in the form of a cumulative demand curve. To adapt the power system capacity to the demand, new power architecture is predicted. To build this latter, the reliability optimization plays an important role to find the realizable power system architecture. This chapter describes and uses different meta-heuristics optimization methods to solve the redundancy optimization problem for multi-state series-parallel power systems. The authors consider the case where redundant power components are chosen to achieve a desirable level of reliability. The power components of the system are characterized by their cost, capacity, and reliability. The proposed meta-heuristics seek the optimal architectures of series-parallel power systems in which a multiple choice of components are allowed from a list of products available in the market. The approach has the advantage of allowing power components with different parameters to be allocated in power systems. To allow fast reliability estimation, a Moment Generating Function (MGF) method is applied. An illustrative example is presented.

[1]  Yan Ping.  An underwater terrain matching arithmetic based on particle filter , 2008 .

[2]  Zong Woo Geem,et al.  Optimal Design of Water Distribution Networks Using Parameter-Setting-Free Harmony Search for Two Major Parameters , 2011 .

[3]  E. Châtelet,et al.  Efficient harmony search algorithm for multi-stages scheduling problem for power systems degradation , 2010 .

[4]  M. Fesanghary,et al.  An improved harmony search algorithm for solving optimization problems , 2007, Appl. Math. Comput..

[5]  M. Mahdavi,et al.  ARTICLE IN PRESS Available online at www.sciencedirect.com , 2007 .

[6]  Emad El-Neweihi,et al.  Degradable systems:a survey of multistate system theory , 1984 .

[7]  Way Kuo,et al.  An annotated overview of system-reliability optimization , 2000, IEEE Trans. Reliab..

[8]  Z. Geem.  Optimal Design of Water Distribution Networks Using Harmony Search , 2009 .

[9]  Fernando José Von Zuben,et al.  Learning and optimization using the clonal selection principle , 2002, IEEE Trans. Evol. Comput..

[10]  K. Lee,et al.  A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice , 2005 .

[11]  Ayaho Miyamoto,et al.  APPLICATION OF THE IMPROVED IMMUNE ALGORITHM TO STRUCTURAL DESIGN SUPPORT SYSTEM , 2004 .

[12]  Anil Kumar Tripathi,et al.  Maximizing reliability of distributed computing system with task allocation using simple genetic algorithm , 2001, J. Syst. Archit..

[13]  Alice E. Smith,et al.  Penalty guided genetic search for reliability design optimization , 1996 .

[14]  Andries P. Engelbrecht.  Heterogeneous Particle Swarm Optimization , 2010, ANTS Conference.

[15]  Mahamed G. H. Omran,et al.  Global-best harmony search , 2008, Appl. Math. Comput..

[16]  Katia Lucchesi Cavalca,et al.  Availability optimization with genetic algorithm , 2003 .

[17]  J. Corriou,et al.  Global optimization by artificial life : a new technique using genetic population evolution , 1994 .

[18]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[19]  Zbigniew Michalewicz,et al.  Evolutionary Algorithms for Constrained Parameter Optimization Problems , 1996, Evolutionary Computation.

[20]  N. K. Jerne,et al.  The immune system. , 1973, Scientific American.

[21]  Zakhar Maymin.  On a conjecture of Barlow and Proschan concerning reliability bounds , 1987 .

[22]  Mostafa Zandieh,et al.  An immune algorithm approach to hybrid flow shops scheduling with sequence-dependent setup times , 2006, Appl. Math. Comput..

[23]  Bent Natvig,et al.  Multistate reliability theory—a case study , 1986, Advances in Applied Probability.

[24]  D. Dasgupta.  Artificial Immune Systems and Their Applications , 1998, Springer Berlin Heidelberg.

[25]  Galit Levitin,et al.  Structure optimization of power system with different redundant elements , 1997 .

[26]  D. Elmakis,et al.  Power system structure optimization subject to reliability constraints , 1996 .

[27]  B. Natvig.  Two suggestions of how to define a multistate coherent system , 1982, Advances in Applied Probability.

[28]  Qinghai Bai,et al.  Analysis of Particle Swarm Optimization Algorithm , 2010, Comput. Inf. Sci..

[29]  Zong Woo Geem,et al.  Harmony Search for Generalized Orienteering Problem: Best Touring in China , 2005, ICNC.

[30]  Xin-She Yang.  Harmony Search as a Metaheuristic Algorithm , 2009 .

[31]  Gregory Levitin,et al.  A new approach to solving problems of multi‐state system reliability optimization , 2001 .

[32]  C. Hwang,et al.  Optimization Techniques for System Reliability with RedundancyߞA Review , 1977, IEEE Transactions on Reliability.