Minimizing Labor Requirements in a Periodic Vehicle Loading Problem |
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Authors: | Email author" target="_blank">Cristina?DelgadoEmail author Manuel?Laguna Joaquín?Pacheco |
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Institution: | (1) Departamento de Economía Aplicada, Universidad de Burgos, Spain;(2) Leeds School of Business, University of Colorado, Boulder, CO 80309-0419, USA;(3) Departamento de Economía Aplicada, Universidad de Burgos, Spain |
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Abstract: | In this paper, we address a logistics problem that a manufacturer of auto parts in the north of Spain described to the authors.
The manufacturer stores products in its warehouse until customers retrieve them. The customers and the manufacturer agree
upon an order pickup frequency. The problem is to find the best pickup schedule, which consists of the days and times during
the day that each customer is expected to retrieve his/her order. For a given planning horizon, the optimization problem is
to minimize the labor requirements to load the vehicles that the customers use to pick up their orders. Heuristically, we
approach this situation as a decision problem in two levels. At the first level, customers are assigned to a calendar, consisting
of a set of days with the required frequency during the planning horizon. Then, for each day, the decision at the second level
is to assign each customer to a time slot. The busiest time slot determines the labor requirement for a given day. Therefore,
once customers have been assigned to particular days in the planning horizon, the second-level decision is a multiprocessor
scheduling problem, where each time slot is the equivalent of a processor, and where the objective is to minimize the makespan.
A metaheuristic procedure is developed for the problem of minimizing labor requirements in this periodic vehicle-loading problem
and artificial as well as real data are used to assess its performance. |
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Keywords: | logistics periodic vehicle-loading problem labor requirements multiprocessor scheduling metaheuristics scatter search |
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