Bee Colony Optimization for Maximum Diversity Problem with Capacity and Budget Constraints

Abstract

The paper explores the problem of selecting a diverse set of points from a given set, with applications in various fields, including facility positioning and renewable energy infrastructure. Specifically, the Maximum Diversity Problem with Capacity and Budget Constraints (MDP-CBC) is addressed, which balances diversity, budget, and capacity limitations in resource allocation. The paper presents an in-depth analysis of the problem, introduces Bee Colony optimization (BCO) as a novel approach, and conducts computational experiments to assess its performance. Results are compared with local search-based methods, demonstrating the potential of BCO in solving MDP-CBC. The paper provides insights into solution representations, neighborhoods, and the implementation of the BCO algorithm. Experimental results on small and medium-sized instances highlight the advantages and disadvantages of the BCO in terms of objective function values. This research contributes to optimizing resource allocation in areas such as renewable energy and facility management.