Edge boundary variable neighborhood strategy adaptive search for a vegetable crop land allocation problem. Issue 3 (3rd July 2022)

• Record Type: Journal Article
• Authors: Nitisiri, Krisanarach; Sethanan, Kanchana; Pitakaso, Rapeepan; Gen, Mitsuo
• Is Part Of: International journal of management science and engineering management. Volume 17:Issue 3(2022)
• Page Start: 166
• Page End: 174
• Publication Date: 2022-07-03
• Subjects: Variable neighborhood strategy adaptive search -- cooperatives crop planning -- modified differential evolution algorithm -- large neighborhood search; Management science -- Periodicals; Engineering -- Management -- Periodicals; Engineering -- Management; Management science; Periodicals; 658.005
• DOI: 10.1080/17509653.2022.2043198
• Languages: English
• ISSNs: 1750-9661

Abstract

ABSTRACT: This paper focuses on optimizing cropland allocation for planting vegetables for farmer cooperatives. In this research, planning about land allocation for crops including what to grow and what is in demand during specific periods is performed while considering important factors such as production yield per area, crop planting and harvesting time, price fluctuations of vegetables and plant incompatibility, so that farmers can plan their crops accordingly, and achieve the optimal prices and annual income. To solve the problem, the Edge Boundary Variable Neighborhood Strategy Adaptive Search (EB-VaNSAS), which is the first extension of Variable Neighborhood Strategy Adaptive Search (VaNSAS), was applied to significantly improve the solution quality of the traditional Variable Neighborhood Strategy. Two local searches, called Track Transition Method (TTM) and Multiplier Factor (MF) were developed and used for the first time in this paper. The numerical results show that the EB-VaNSAS outperforms all other proposed methods since EB-VaNSAS could find new optimal solutions more often during the simulation, while the local search-based heuristics tend to be trapped in some local optima, and the DE lacks search intensification.