A meta-heuristic approach to car allocation problem to reduce transportation cost over a fixed number of routes
AbstractThis study addresses the problem of car allocation to different routes under certain restrictions with the objective of reducing the excess cost of transportation. A meta-heuristic approach based on Ant Colony Optimisation (ACO) algorithm is proposed and implemented to schedule the cars efficiently along the routes under the existing logistics. A mathematical model with two objectives is formulated for this purpose and solved in two phases. In the first phase, sequences of allocated cars are determined while in the second, car allocation scheme for each trip is determined using ACO algorithm. The simulation study is carried out from the empirical distributions of distance and time, followed by the sensitivity analysis on the basis of their stochastic behaviour. The cost benefit analysis shows a projected savings in terms of reduction of cost of travel, both with respect to distance and time, through the solutions obtained.
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Bibliographic InfoArticle provided by Inderscience Enterprises Ltd in its journal Int. J. of Data Analysis Techniques and Strategies.
Volume (Year): 2 (2010)
Issue (Month): 1 ()
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Web page: http://www.inderscience.com/browse/index.php?journalID=282
routes; trips; ant colony optimisation; ACO; idle time; excess time; excess cost; sensitivity analysis; metaheuristics; car allocation; transport costs; scheduling; logistics; mathematical modelling.;
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