Highlights Consider round-trip transportation and the optimal trail-and error visiting strategy in reliable location design. Propose a scalable continuum approximation (CA) model. Analyze theoretical properties of CA in solution optimality bounds. Compare CA with the discrete and continuous models. Reveal managerial insights into optimal location design and costs.
Abstract The Part I paper (Yun et al., 2019) of this study developed a discrete model and a customized Lagrangian relaxation algorithm for the reliable problem of facility locations considering round-trip transportation when customers are not aware of facility states in real time until they visit them on site. Since the investigated problem is an NP-hard problem, large-scale instances of this problem may not be solved efficiently by the discrete model. To address this issue, this paper proposes a counterpart continuous model to solve large-scale instances of the investigated problem. The continuous model assumes that all the settings are continuous and adopts the continuum approximation (CA) technique to obtain a near-optimum solution to this investigated problem. The CA technique also reveals theoretical insights into solution structures of each sub-problem on a customer's pattern of visiting facilities on a homogeneous plane. Numerical experiments find that the continuous model with the CA technique has superior computational efficiency for large-scale instances. The results of the case studies indicate that the proposed continuous model can obtain a near-optimum solution for the investigated location problem with heterogeneous settings and has a robust performance.
Reliable facility location design with round-trip transportation under imperfect information part II: A continuous model
Transportation Research Part B: Methodological ; 124 ; 44-59
2019-04-08
16 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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