Transfer of manure as fertilizer from livestock farms to crop fields: The case of Catalonia

被引:15
作者
Kamilaris, Andreas [1 ,2 ]
Engelbrecht, Andries [5 ]
Pitsillides, Andreas [4 ]
Prenafeta-Boldu, Francesc X. [3 ]
机构
[1] Res Ctr Interact Media Smart Syst & Emerging Tech, Nicosia, Cyprus
[2] Univ Twente, Dept Comp Sci, Enschede, Netherlands
[3] Inst Agr & Food Res & Technol IRTA, Barcelona, Spain
[4] Univ Cyprus, Dept Comp Sci, Nicosia, Cyprus
[5] Univ Stellenbosch, Dept Ind Engn, Stellenbosch, South Africa
基金
欧盟地平线“2020”;
关键词
Animal manure; Livestock farming; Environmental impact; Logistic problem; Optimization; Nature-inspired; Ant behaviour; VEHICLE-ROUTING PROBLEM; ANIMAL MANURE; MANAGEMENT; COLONY; OPTIMIZATION; POLLUTION; SYSTEM; AREAS; GIS;
D O I
10.1016/j.compag.2020.105550
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Intensive livestock production might have a negative environmental impact, by producing large amounts of animal manure, which, if not properly managed, can contaminate nearby water bodies with nutrient excess. However, if animal manure is exported to nearby crop fields, to be used as organic fertilizer, pollution can be mitigated. It is a single-objective optimization problem, in regards to finding the best solution for the logistics process of satisfying nutrient needs of crops by means of livestock manure. This paper proposes three different approaches to solve the problem: a centralized optimal algorithm (COA), a decentralized nature-inspired cooperative technique, based on the foraging behaviour of ants (AIA), as well as a naive neighbour-based method (NBS), which constitutes the existing practice used today in an ad hoc, uncoordinated manner in Catalonia. Results show that the COA approach is 8.5% more efficient than the AIA. However, the AIA approach is fairer to the farmers and more balanced in terms of average transportation distances that need to be covered by each livestock farmer, while it is 1.07 times more efficient than the NBS. Our work constitutes the first application of a decentralized AIA to this interesting real-world problem, in a domain where swarm intelligence methods are still under-exploited.
引用
收藏
页数:11
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