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Location and reliability problems on a line: Impact of objectives and correlated failures on optimal location patterns

by: Oded Berman, Dmitry Krass, Mozart B. C. Menezes
Omega (October 2012), doi:10.1016/j.omega.2012.09.002  Key: citeulike:11564422

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Abstract

In this paper we study a class of locations models where facilities are not perfectly reliable and failures may be correlated. We analyze problems with Median and Center objectives under complete and incomplete customer information regarding the state of facilities. The goal is to understand how failure probabilities, correlations, availability of information and problem objective affect the optimal location patterns. In particular, we want to find analytical confirmations for location patterns observed in numerical experiments with network location models. To derive closed-form analytical results the analysis is restricted to a simple (yet classic) setting: a 2-facility problem on a unit segment, with customer demand distributed uniformly over the segment (results can be extended to other demand distributions as well). We derive explicit expressions for facility trajectories as functions of model parameters, obtaining a number of managerial insights. In addition we provide the decomposition of the optimal cost into the closed form components corresponding to the cost of travel, the cost of facility unreliability and the cost of incomplete information. Most of the theoretical insights are via numerical experiments for models with larger (3–5) number of facilities. ⺠Study of locations models where facilities are not perfectly reliable and failures may be correlated. ⺠Analysis of the Median and Center objectives under complete and incomplete customer information. ⺠Analysis of how failure probabilities, correlationsand information affect the optimal location patterns. ⺠Shows facility trajectories analytically as functions of model parameters providing managerial insights. ⺠Decompose the cost into the cost of travel, the cost of facility unreliability and the cost of incomplete information.


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