Abstract
Agricultural tourism is considered a means of providing motor for growth in rural areas and year-round tourism flow, promoting local products and SMEs, encouraging the diversification of economic activity and in the long run a way of improving the quality of life in rural areas. For more than three decades now this concept goes hand to hand with avoiding/preventing the social and economic collapse of rural areas, and with multi-functionality. Ιncreasing interest in tourism, tourism in rural areas and thematic tourism as well as tourists seeking fast and accurate information has led to the proposal of personalized (team) tours, rather than generic ones, with the use of recommender and geo-informatic systems alongside with smart applications, web services, context and location based services. Τo provide maximum functionality to users and engage them into using a service it is needed to represent/model the real daily multi-dimensional activities of a tourist during a trip with more than one objective function. Crucial to such a service are the formulations that model tourist trip problems, and the algorithms that generate and optimize the proposed tours. Therefore, this comprehensive review explores the multi-objective nature of agricultural touring, and focuses on multi-objective formulations that arose in the literature so far in touring, especially concerning tourism, and in regard of them being applied under agri-touristical scenarios. Under the scope of multi-objective optimization, we focus also in the related Orienteering and Team Orienteering Problem (OP/TOP). We consider selected non-dynamic/dynamic multi-objective route planning problems/methods, variants of the OP and TOP for route planning and scheduling problems, as well as for tourism and agricultural tourism, and the algorithms proposed and/or tested for the latter.
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Abbreviations
- BOOP:
-
Bi-objective orienteering problem
- BOP:
-
Bi-orienteering problem
- EA:
-
Evolutionary algorithm
- EMO:
-
Evolutionary multi-objective
- EU:
-
European Union
- GRASP:
-
Greedy randomized adaptive search procedure
- MDLS:
-
Multi directional local search
- MOOP:
-
Multi objective orienteering problem
- MOTDOP:
-
Multi-objective time-dependent orienteering problem
- NSGA-II:
-
Non-dominated sorting genetic algorithm II
- OP:
-
Orienteering problem
- P-ACO:
-
Pareto ant colony optimization
- POI:
-
Point of interest
- PR:
-
Path relinking
- P-VNS:
-
Pareto variable neighborhood search
- SME:
-
Small and medium-sized enterprises
- TOP:
-
Team orienteering problem
- TTDP:
-
Tourist trip design problem
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Diareme, K.C., Tsiligiridis, T. (2018). Multi-criteria Optimization Methods Applied in Agricultural Touring. In: Berbel, J., Bournaris, T., Manos, B., Matsatsinis, N., Viaggi, D. (eds) Multicriteria Analysis in Agriculture. Multiple Criteria Decision Making. Springer, Cham. https://doi.org/10.1007/978-3-319-76929-5_11
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