A Membership Function Approach for Cost-Reliability Trade-Off of Cots Selection in Fuzzy Environment

Abstract

The optimization techniques used in commercial-off-the-shelf (COTS) selection process faces challenges to deal with uncertainty in many important selection parameters, for example, cost, reliability and delivery time. In this paper, we propose a fuzzy optimization model for selecting the best COTS product among the available alternatives for each module in the development of modular software systems. The proposed model minimizes the total cost of the software system satisfying the constraints of minimum threshold on system reliability, maximum threshold on the delivery time of the software, and incompatibility among COTS products. In order to deal with uncertainty in real-world applications of COTS selection, the coefficients of the cost objective function, delivery time constraints and minimum threshold on reliability are considered fuzzy numbers. The fuzzy optimization model is converted into a pair of mathematical programming problems parameterized by possibility (feasibility) level α using Zadeh's extension principle. The solutions of the resultant problems at different α-cuts provide lower and upper bounds of the fuzzy minimum total cost which helps in constructing the membership function of the cost objective function. The solution approach provide fuzzy solutions instead of a single crisp solution thereby giving decision maker enough flexibility in maintaining cost-reliability trade-off of COTS selection besides meeting other important system requirements. A real-world case study is discussed to demonstrate the effectiveness of the proposed model in fuzzy environment.

MCDM based evaluation and ranking of commercial off-the-shelf using fuzzy based matrix method

“…Kunda and Brooks (1999) (2003) Tradeoff) for the COTS selection, implementation and governance by focusing on benefits to the customer organization and system Integrator. Gupta et al (2013Gupta et al ( , 2011 has developed a systematic and interactive Fuzzy Optimization framework for the solution of bi-objective fuzzy COTS selection. Kaur and Singh (2014) used PROMETHEE whereas Nazir et al (2014) used Analytic Network Process approach for the selection of COTS.…”

“…Baharom et al (2012) introduced vendor characteristics such as vendor stability, vendor reputation, vendor supportability and organization characteristics as system platform, development environment, culture and financial characteristic for COTS component selection. Gupta et al (2013Gupta et al ( , 2011 used quality, cost, probability of failure on demand, average number of invocations, number of lines of code, execution time, delivery time and quality characteristics as selection criteria. The COTS selection criteria are generally into four major groups, namely quality characteristics, technology factors, domain and architectural factors and strategic factors.…”

COTS products selection using fuzzy chance-constrained multiobjective programming

“…. , sc 1n 1 are available to implement module 1, and so on [9]. Formulation of the COTS products selection problem requires estimating several important parameters, namely, the cost, size, execution time, and delivery time for available COTS products.…”

“…In this section, we discuss a real-life problem based on an industrial case scenario adopted from Gupta et al [9] to demonstrate the applicability of the COTS selection model and the proposed solution approach. A local software system supplier plans to develop an enterprise resource planning (ERP) software system for small-and medium-sized enterprises.…”

“…Gupta et al [8] developed fuzzy multiobjective optimization models to select optimal COTS software products using multiple methodologies, such as quality models, analytical hierarchy process and fuzzy mathematical programming. Gupta et al [9] proposed a fuzzy optimization model to select the best COTS product among the available alternatives for each module in the development of modular software systems. Jha et al [14] developed an optimization model for selecting COTS components that maximizes reliability and minimizes absolute deviational execution time, which in turn minimizes the overall execution time of the software system.…”