In computer science and operations research, harmony search (HS) is a phenomenon-mimicking algorithm (also known as meta-heuristic algorithm, soft computing algorithm or evolutionary algorithm) inspired by the improvisation process of musicians. In the HS algorithm, each musician (= decision variable) plays (= generates) a note (= a value) for finding a best harmony (= global optimum) all together. Proponents claim the following merits: 1. HS does not require differential gradients, thus it can consider discontinuous functions as well as continuous functions. 2. HS can handle discrete variables as well as continuous variables. 3. HS does not require initial value setting for the variables. 4. HS is free from divergence. 5. HS may escape local optima.
Published in Chapter:
A Comparison for Optimal Allocation of a Reliability Algorithms Production System
Abdelkader Zeblah (University of Sidi Bel Abbes, Algeria), Abdelkader Rami (University of Sidi Bel Abbes, Algeria), and Eric Châtelet (University of Technology of Troyes, France)
Copyright: © 2015
|Pages: 30
DOI: 10.4018/978-1-4666-7258-1.ch018
Abstract
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.