M. Bender, J. Kalcsics, A. Meyer
In sales districting, the task is to assign a given set of (prospective) customer accounts, each with a fixed market potential, to the individual members of a sales force such that each customer has a unique representative, each sales person faces an equitable workload and has an equal income opportunity in terms of incentive pay, and travel times are minimal. Concerning the travel times, if a sales person visits each customer every day, then the travel time is proportional to the length of a TSP tour. However, the workload of districts is usually balanced over several weeks and some customers may have to be visited only once during this time whereas others require weekly service. Moreover, customers may have time windows, tours may include overnight stays, and so on, which makes the actual computation of the travel times almost impossible. Hence, in most cases one has to rely on estimates. The most common estimate in the literature is to compute either the sum of distances between a sales person's location and his assigned customers or the sum of pairwise distances between all customers assigned to the sales person.
In this talk we extend the classical formulation for sales districting by explicitly taking into account different visiting frequencies for customers. This introduces a time as well as a scheduling component into the problem. We present a straight forward ILP formulation for this problem and some preliminary computational results. As just very, very small instances can be solved optimally using this formulation, we propose to decompose the problem and apply a location-allocation based heuristic.
Keywords: Sales districting, multi-period scheduling, decomposition
Scheduled
T1 Combinatorial Optimization 2
October 1, 2015 9:30 AM
Salón de actos
