Swarm Intelligence in Optimal Management of Aquaculture Farms

A. Cobo (), I. Llorente and L. Luna
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A. Cobo: University of Cantabria
I. Llorente: University of Cantabria
L. Luna: University of Cantabria

Chapter Chapter 10 in Handbook of Operations Research in Agriculture and the Agri-Food Industry, 2015, pp 221-239 from Springer

Abstract: Abstract Optimization techniques inspired by swarm intelligence (SI) have become increasingly popular during the last two decades. These techniques are based on the idea that groups of extremely simple agents with little or no organization can exhibit complex and intelligent behavior by using simple local rules and communication mechanisms. Thanks to this intelligent behavior, a group of social agents can carry out actions on a complex level and form decentralized and self-organizational systems. The advantage of these optimization approaches over traditional techniques is their robustness and flexibility, making SI especially appropriated to deal with complex optimization problems. In this chapter we introduce the concept of computational swarm intelligence; we present an overview of the most important optimization techniques inspired by swarm intelligence and examine the research contributions to the application of SI metaheuristics in different problems related to optimal management of aquaculture farms. As example of application we will present a particle swarm optimization (PSO) algorithm based on a bioeconomic model that helps managers of aquaculture enterprises in the process of decision-making, maximizing gross margin and minimizing operational risk.

Keywords: Particle Swarm Optimization; Particle Swarm Optimization Algorithm; Travel Salesman Problem; Swarm Intelligence; Bioeconomic Model (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-1-4939-2483-7_10

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