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Towards a framework for fishing route optimization decision support systems: Review of the state-of-the-art and challenges.
- Source :
-
Journal of Cleaner Production . Oct2021, Vol. 320, pN.PAG-N.PAG. 1p. - Publication Year :
- 2021
-
Abstract
- Route optimization methods offer an opportunity to the fisheries industry to enhance their efficiency, sustainability, and safety. However, the use of route optimization Decision Support Systems (DSS), which have been widely used in the shipping industry, is limited in the case of fisheries. In the first part, this work describes the fishing routing problems, reviews the state-of-the-art methods applied in the shipping industry, and introduces a general framework for fishing route optimization decision support systems (FRODSS). In the second part, we highlight the existing gap for the application of DSS in fisheries, and how to develop a FRODSS considering the different types of fishing fleets. Finally, and using the diverse Basque fishing fleet as a case study, we conclude that fishing fleets can be summarized into four main groups whose fishing routes could be optimized in a similar way. This characterization is based on their similarities, such us the target species, fishing gear, and the type and distance to the fishing grounds. These four groups are: (i) small-scale coastal fleet; (ii) large-scale pelagic fleet; (iii) large-scale demersal fleet; and (iv) the distant-water fleet. Distant-water vessels are currently the fleet that can more easily benefit from FRODSS, and they are used as an example here. However, the rest of the fleets could also benefit through adequate adaptation to their operation characteristics, driven by their specific fishing gear and target species. [ABSTRACT FROM AUTHOR]
- Subjects :
- *DECISION support systems
*MARITIME shipping
*FISHING
*FISHERIES
*FISH industry
Subjects
Details
- Language :
- English
- ISSN :
- 09596526
- Volume :
- 320
- Database :
- Academic Search Index
- Journal :
- Journal of Cleaner Production
- Publication Type :
- Academic Journal
- Accession number :
- 152681582
- Full Text :
- https://doi.org/10.1016/j.jclepro.2021.128661