Skip to content
Research Article Open access CC BY 4.0

Genetic Algorithm Based Hybrid Approach to Solve Optimistic, Most-likely and Pessimistic Scenarios of Fuzzy Multi-objective Assignment Problem Using Exponential Membership Function

Anita Ravi Tailor, Jayesh M. Dhodiya

Journal of Advances in Mathematics and Computer Science · pp. 1–19 · Published 11 Jun 2016

10.9734/BJMCS/2016/26988

Abstract

This paper discussed a genetic algorithm based hybrid approach to solve different scenario (optimistic scenario, most-likely scenario and pessimistic scenario) of fuzzy multi-objective assignment problem (FMOAP) using an exponential membership function in which coefficient of the objective function is described by triangular possibilities distribution (TDP). Moreover, we used the α-level sets to classify the fuzzy judgment for Decision maker (DM) to optimize different scenario of fuzzy objective functions. We used a fuzzy technique to solve multi-objective optimization problem in which DM is required to specify the indistinct aspiration level as per the his/her preference and genetic algorithm is used to solve the 0-1 optimization problem for different choices of shape parameter in the exponential membership function. A numerical example is provided to demonstrate the effectiveness of the proposed approach with data set form realistic situation.

Assignment problem α-level sets optimistic scenario most likely scenario pessimistic scenario exponential membership function genetic algorithm.

Cited by 8

Design and Development of a Genetic Algorithm Based on Fuzzy Inference Systems for Personnel Assignment Problem

Peyman Rabiei, Daniel Arias-Aranda · WPOM-Working Papers on Operations Management · 2021

Aspiration level-based non-dominated sorting genetic algorithm II & III to solve fuzzy multi-objective shortest path problem

Aniket Todkar, Jayesh Dhodiya · Yugoslav Journal of Operations Research · 2025

Solution of fuzzy multi criteria project management problem by Fuzzy programming technique with possibilistic approach

Riddhi K. Rekh, Jayesh M. Dhodiya, RNGPIT, Isroli, Bardoli � 394620, Gujarat, India; · Indian Journal of Science and Technology · 2019

Genetic algorithm based hybrid approach to solve uncertain multi-objective COTS selection problem for modular software system

Jayesh M. Dhodiya, Anita Ravi Tailor · Journal of Intelligent & Fuzzy Systems · 2018

GA-Based Hybrid Approach to Solve Fuzzy Multi-objective Optimization Model of Multi-application-Based COTS Selection Problem

Anita Ravi Tailor, Jayesh M. Dhodiya · Advances in Intelligent Systems and Computing · 2019

Multi-objective Assignment Problems and Their Solutions by Genetic Algorithm

Anita R. Tailor, Jayesh M. Dhodiya · Modeling and Optimization in Science and Technologies · 2021

A genetic algorithm based approach to solve multi-resource multi-objective knapsack problem for vegetable wholesalers in fuzzy environment

Chiranjit Changdar, Rajat Kumar Pal, Ghanshaym Singha Mahapatra · Operational Research · 2018

Genetic algorithm based hybrid approach to solve fuzzy multi-objective assignment problem using exponential membership function

Jayesh M. Dhodiya, Anita Ravi Tailor · SpringerPlus · 2016

Related research

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

8

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.