{"title":"ANT COLONY OPTIMIZATION: AN ECONOMIC TRANSPOSITION","authors":"Vlad Popescu","doi":"10.24818/oec/2021/30/4.02","DOIUrl":null,"url":null,"abstract":"The paper tackles recent developments in the field of social behaviours of insects and swarm intelligence – “stigmergy”. Specifically, this paper aims to explore the paradigm of ant colony optimization from two main perspectives – economic and biological – so that we can attain a clear view of the genomic bases that allow ants to function as complex biological navigation systems. Such systems translate nowadays into metaheuristic algorithms whose purpose is to solve extremely difficult combinatorial optimization problems. The design of these algorithms draws inspiration from the foraging behaviour of real ants. In the case study, an example of using an ant colony optimization algorithm in order to solve a routing problem shows us how only two iterations and two ants were enough to reveal the shortest path, taking into consideration the amount of pheromones emitted.","PeriodicalId":43088,"journal":{"name":"Argumenta Oeconomica","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Argumenta Oeconomica","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.24818/oec/2021/30/4.02","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
The paper tackles recent developments in the field of social behaviours of insects and swarm intelligence – “stigmergy”. Specifically, this paper aims to explore the paradigm of ant colony optimization from two main perspectives – economic and biological – so that we can attain a clear view of the genomic bases that allow ants to function as complex biological navigation systems. Such systems translate nowadays into metaheuristic algorithms whose purpose is to solve extremely difficult combinatorial optimization problems. The design of these algorithms draws inspiration from the foraging behaviour of real ants. In the case study, an example of using an ant colony optimization algorithm in order to solve a routing problem shows us how only two iterations and two ants were enough to reveal the shortest path, taking into consideration the amount of pheromones emitted.
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