Title: Adapting the artificial bee colony metaheuristic to solve multi-objective problems

Authors: Saima Dhouib; Souhail Dhouib; Habib Chabchoub

Addresses: LOgistic Genie Industrial and Quality (LOGIQ) Research Laboratory, Sfax University, Tunisia ' Department of Operations and Information Management, College of Business, Effat University, Saudi Arabia ' Department of Quantitative Methods, Faculty of Management and Economics Sciences, Sfax University, Tunisia

Abstract: In this paper, an artificial bee colony (ABC) metaheuristic is adapted to find Pareto optimal set solutions for goal programming problems. The proposed algorithm is named weighted goal programming artificial bee colony (WGP-ABC). This WGP-ABC is personalised to support the MOO by means of a weighted sum formulation for the objective function: solving several scalarisations of the objective function according to a weight vector with non-negative components. The efficiency of the proposed approach is demonstrated by nonlinear engineering design problems. In all problems, multiple solutions to the goal programming problem are found in short computational time using very few user-defined parameters.

Keywords: goal programming; multi-objective optimisation; continuous work space; metaheuristics; artificial bee colony; ABC; nonlinear design; engineering design.

DOI: 10.1504/IJMTM.2015.071232

International Journal of Manufacturing Technology and Management, 2015 Vol.29 No.5/6, pp.366 - 380

Received: 09 Jan 2015
Accepted: 14 May 2015

Published online: 17 Aug 2015 *

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