Introducing the Dynamic Customer Location-Allocation Problem

Abstract

In this paper, we introduce a new stochastic Location-Allocation Problem which assumes the movement of customers over time. We call this new problem Dynamic Customer Location-Allocation Problem (DC-LAP). The problem is based on the idea that customers will change locations over a defined horizon and these changes have to be taken into account when establishing facilities to service customers demands. We generate 1440 problem instances by varying the problem parameters of movement rate which determines the possible number of times a customer will change locations over the defined period, the number of facilities and the number of customers. We propose to analyse the characteristics of the instances generated by testing a search algorithm using the stochastic dynamic evaluation (based on the replication of customer movement scenarios) and a deterministic static evaluation (based on the assumption that customer will not move over time). We show that the dynamic approach obtains globally better results, but the performances are highly related to the parameters of the problem. Moreover, the dynamic approach involves a significantly high computational overhead.

Robust Optimization Over Time: A Critical Review

“…While progress has been made in developing algorithms, much work remains to be done before the field can fully address the challenges of real-world problems. Currently, the performance of algorithms is typically evaluated using artificial benchmark problems and some existing ROOT methods have been applied to real-world-based benchmark problems, including nonlinear dynamic stochastic optimization problems for stochastic energy management [102,103] and dynamic customer location-allocation [104,105]. One of the main challenges in solving real-world problems is that dynamic handling components are not yet capable of handling the complexities of these problems, such as irregular changes over time, multiple types of environmental changes, local and hardto-detect environmental changes, and continuously changing environments.…”