Computational Intelligence in Reliability Engineering New by Gregory Levitin

By Gregory Levitin

This quantity includes chapters providing functions of other metaheuristics (ant colony optimization, nice deluge set of rules, cross-entropy approach and particle swarm optimization) in reliability engineering. it is also chapters dedicated to mobile automata and aid vector machines and various functions of synthetic neural networks, a robust adaptive procedure that may be used for studying, prediction and optimization. numerous chapters describe varied points of obscure reliability and purposes of fuzzy and imprecise set conception.

Show description

Read Online or Download Computational Intelligence in Reliability Engineering New Metaheuristics Neural and Fuzzy Techniques in Reliability PDF

Best industrial engineering books

Maynard's Industrial Engineering Handbook

The main whole, functional operating consultant to the rules, equipment, fabrics, and structures of business engineering on hand. The 5th variation of Maynard's is a daring new reference for a colourful occupation. Designed for commercial engineers who're challenged to do extra, in additional arenas, this re-creation of an pillar offers you:*Focus on functional functions of latest equipment and technologies*Succinct articles and summaries with outstanding indexing that yield the knowledge you will have quickly*Inclusive assurance of every little thing from the evolution of business engineering to important advancements in CAD/CAM, with the emphasis on productivity*More than 20 full-scale case reports with distinctive closeups of real-world software successes

Maintenance Planning and Scheduling: Streamline Your Organization for a Lean Environment

It is a hands-on reference consultant for the upkeep or reliability engineer and plant supervisor. because the 3rd quantity within the "Life Cycle Engineering" sequence, this e-book takes the guiding rules of Lean production and upkeep and applies those innovations to daily making plans and scheduling initiatives permitting engineers to maintain their apparatus operating easily, whereas lowering downtime.

Solutions Manual to Accompany Introduction to Linear Regression Analysis

Because the recommendations handbook, this booklet is intended to accompany the most title, Introduction to Linear Regression research, 5th Edition. Clearly balancing thought with purposes, this publication describes either the traditional and not more universal makes use of of linear regression within the functional context of ultra-modern mathematical and medical learn.

Pneumatic Conveying Design Guide, Third Edition

Pneumatic Conveying layout advisor, third variation is split into 3 crucial components, method and elements, process layout, and process operation, offering either crucial foundational wisdom and useful info to assist clients comprehend, layout, and construct appropriate platforms. All features of the pneumatic conveying procedure are lined, together with the kind of fabrics used, conveying distance, procedure constraints, together with feeding and discharging, wellbeing and fitness and safeguard requisites, and the necessity for non-stop or batch conveying.

Extra resources for Computational Intelligence in Reliability Engineering New Metaheuristics Neural and Fuzzy Techniques in Reliability

Example text

1 Introduction Optimization of reliability of complex systems is an extremely important issue in the field of reliability engineering. Over the past three decades, reliability optimization problems have been formulated as non-linear programming problems within either single-objective or multi-objective environment. Tillman et al.. (1980) provides an excellent overview of a variety of optimization techniques applied to solve these problems. However, he reviewed the application of only derivative-based optimization techniques, as metaheuristics were not applied to the reliability optimization problems by that time.

3 (3) Monte Carlo Simulation The evaluation of network reliability in general is a #P-complete problem. , via (2), is not feasible, estimation via Monte Carlo simulation becomes a viable option. The easiest way to estimate the reliability r (or unreliability r ) is to use CMC simulation, that is, let X(1),…,X(N) be independent identically distributed random vectors with the same distribution as X. Then rˆCMC = 1 N N ∑ϕ ( X ) i =1 (i ) is an unbiased estimator of r. Its sample variance is given by 46 Dirk P.

This information is missing for other algorithms. 823562 with 20,100 function evaluations. 9 is obtained in both cases. Thus, for this problem, ACO obtained a marginal improvement over MGDA in terms of accuracy and also consumed far less function evaluations. , 1980) in terms of both accuracy and speed. Table 1. Results of Problem 1- Case (i) Solution R1 R2 R3 R4 RS CS FE* Ravi (2004) MGDA ACO Shelokar et al. (2002) INESA Ravi et al. 8332 NA SA Ravi et al. 903 NA Tillman et al. 570892 with 54,140 function evaluations.

Download PDF sample

Rated 4.02 of 5 – based on 42 votes

Categories: Industrial Engineering