Summary
We discuss a class of large-scale real-world field service optimization problems which may be described as generalizations of the Vehicle Routing Problem with Time Windows (VRPTW). We describe our experience in the real-world issues concerned with describing and solving instances of such problems, and adapting the solution to the needs of service organizations using a ”universal framework” for bringing together various problem representations and experimenting with different algorithms. Implementations and results of several bio-inspired approaches are discussed: Genetic Algorithm (GA), Ant Colony Optimization (ACO), and a hybrid of ACO with GRASP (Greedy Randomized Adaptive Search Procedure). We conclude by discussing generation of ”human-friendly” solutions, through introduction of local considerations into the global optimization process.
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Beniaminy, I., Yellin, D., Zahavi, U., Žerdin, M. (2009). When the Rubber Meets the Road: Bio-inspired Field Service Scheduling in the Real World. In: Pereira, F.B., Tavares, J. (eds) Bio-inspired Algorithms for the Vehicle Routing Problem. Studies in Computational Intelligence, vol 161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85152-3_9
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DOI: https://doi.org/10.1007/978-3-540-85152-3_9
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