Mitigating Traffic Congestion: Solving the Ride-Matching Problem by Bee Colony Optimization
Open Access
- 13 March 2008
- journal article
- research article
- Published by Taylor & Francis Ltd in Transportation Planning and Technology
- Vol. 31 (2), 135-152
- https://doi.org/10.1080/03081060801948027
Abstract
Urban road networks in many countries are severely congested. Expanding traffic network capacities by building more roads is very costly as well as environmentally damaging. Researchers, planners, and transportation professionals have developed various Travel Demand Management (TDM) techniques, i.e. strategies that increase travel choices to travelers. Ride sharing is one of the widely used TDM techniques that assumes the participation of two or more persons that together share a vehicle when traveling from few origins to few destinations. In ride-matching systems, commuters wishing to participate in ride sharing are matched by where they live and work, and by their work schedule. There is no standard method in the open literature to determine the best ride-matching method. In this paper, an attempt has been made to develop the methodology capable to solve the ride-matching problem. The proposed Bee Colony Optimization Metaheuristic is sufficiently general and could be applied to various combinatorial optimization problems.This publication has 15 references indexed in Scilit:
- Computing with Bees: Attacking Complex Transportation Engineering ProblemsInternational Journal on Artificial Intelligence Tools, 2003
- Effects of pollen quality and genotype on the dance of foraging honey beesAnimal Behaviour, 1998
- California Route 91 Toll Lanes Impacts and Other ObservationsTransportation Research Record: Journal of the Transportation Research Board, 1998
- Lifetime learning by foraging honey beesAnimal Behaviour, 1994
- The tremble dance of the honey bee: message and meaningsBehavioral Ecology and Sociobiology, 1992
- Learning foraging tasks by bees: a comparison between social and solitary speciesAnimal Behaviour, 1991
- A model of collective nectar source selection by honey bees: Self-organization through simple rulesJournal of Theoretical Biology, 1991
- Assessing the benefits of cooperation in honeybee foraging: search costs, forage quality, and competitive abilityBehavioral Ecology and Sociobiology, 1988
- Landmark learning by honey beesAnimal Behaviour, 1987
- Fuzzy setsInformation and Control, 1965