Abstract

This paper presents an application of interactive fuzzy goal programming to the nonlinear multi-objective reliability optimization problem considering system reliability and cost of the system as objective functions. As the decision maker always have an intention to produce highly reliable system with minimum cost, therefore, we introduce the interactive method to design a high productivity system here. This method plays an important role to maximize the worst lower bound to obtain the preferred compromise solution which is close to the best upper bound of each objective functions. Until the preferred compromise solution is reached, new lower bounds corresponding to each objective functions will be determined based on the present solution to develop the updated membership functions as well as aspiration levels to resolve the proposed problem. Considering judgmental vagueness of decision maker, here we consider the resources as trapezoidal fuzzy numbers and apply total integral value of fuzzy number to transform into crisp one. To illustrate the methodology and performance of this approach, numerical examples are presented and evaluated by comparing with the other method at the end of this paper.

Highlights

  • Since 1960, reliability engineering is one of the most important tasks in designing and development of a technical system

  • The diversity of system resources, resource constraints, and options for reliability improvement leads to the construction and analysis of several optimization models

  • The majority of reliability optimization models discussed in the various literatures

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Summary

Introduction

Since 1960, reliability engineering is one of the most important tasks in designing and development of a technical system. The primary goal of reliability engineer is always to find the best route to increase the system reliability. The diversity of system resources, resource constraints, and options for reliability improvement leads to the construction and analysis of several optimization models. The majority of reliability optimization models discussed in the various literatures. Misra (1971) discussed the application of integer programming to solve reliability optimization problems. Later Kuo and Prasad (2000) and Kuo et al (2001) presented some suitable method for solving reliability optimization models. Hao et al (2017) proposed an efficient and robust algorithm of non-probabilistic reliability-based design optimization (NRBDO). Later an efficient and accurate RBDO framework based on

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