Multi-objective constrained algorithm (MCA) and non-dominated sorting genetic algorithm (NSGA-ii) for solving multi-objective crop planning problem

Jarin, Sams and Khatun, Mst Khaleda and Shafie, Amir Akramin (2016) Multi-objective constrained algorithm (MCA) and non-dominated sorting genetic algorithm (NSGA-ii) for solving multi-objective crop planning problem. ARPN Journal of Engineering and Applied Sciences, 11 (6). pp. 4079-4086. ISSN 1819-6608

	PDF - Published Version Restricted to Repository staff only Download (137kB) | Request a copy
	PDF - Published Version Restricted to Repository staff only Download (248kB) | Request a copy

Abstract

Crop planning problem is a multi-objective optimization problem. It is related to many factors such as land type, capital, demand etc. From very earlier years, people have been trying to find out a best solution for crop planning to get more profit in exchange of less investment and cost. In this paper, we formulate a crop planning problem as a multiobjective optimization model and try to solve two different versions of the problem using two different optimization algorithms MCA and NSGA. In this two algorithms, they provide superior solutions to maximize total net benefit and minimize total cost. We investigate these algorithms here as a linear crop planning model and use them to acquire the maximum total gross margin according with minimum total working capital in order to satisfy some constraints. We also compare the performance of these two algorithms and analyse the solution from the decision-making point of view.

Item Type:	Article (Journal)
Additional Information:	5119/56519
Uncontrolled Keywords:	crop planning problem, multi-objective optimization, evolutionary algorithm.
Subjects:	T Technology > TJ Mechanical engineering and machinery
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechanical Engineering
Depositing User:	Dr Amir Shafie
Date Deposited:	17 Apr 2017 09:24
Last Modified:	17 Apr 2017 09:24
URI:	http://irep.iium.edu.my/id/eprint/56519

Actions (login required)

View Item