An analytical approach to the facility location and capacity acquisition problem under demand uncertainty

2005 ◽  
Vol 56 (4) ◽  
pp. 397-405 ◽  
Author(s):  
A Dasci ◽  
G Laporte
Keyword(s):  
Facility Location ◽  
Analytical Approach ◽  
Demand Uncertainty ◽  
Capacity Acquisition

Two-Facility Location Problem with Infinite Retrial Queue

2012 ◽  
pp. 294-310
Author(s):  
Ebrahim Teimoury ◽  
Mohammad Modarres Yazdi ◽  
Iman Ghaleh Khondabi ◽  
Mahdi Fathi
Keyword(s):  
Steady State ◽  
Facility Location ◽  
Demand Uncertainty ◽  
Location Problem ◽  
Retrial Queue ◽  
Facility Location Problem ◽  
Fixed Cost ◽  
Performance Indexes ◽  
Matrix Geometric Method ◽  
Primary Service

This paper analyzes a two-facility location problem under demand uncertainty. The maximum server for the ith facility is It is assumed that primary service demand arrivals for the ith facility follow a Poisson process. Each customer chooses one of the facilities with a probability which depends on his or her distance to each facility. The service times are assumed to be exponential and there is no vacation or failure in the system. Both facilities are assumed to be substitutable which means that if a facility has no free server, the other facility is used to fulfill the demand. When there is no idle server in both facilities, each arriving primary demand goes into an orbit of unlimited size. The orbiting demands retry to get service following an exponential distribution. In this paper, the authors give a stability condition of the demand satisfying process, and then obtain the steady-state distribution by applying matrix geometric method in order to calculation of some key performance indexes. By considering the fixed cost of opening a facility and the steady state service costs, the best locations for two facilities are derived. The result is illustrated by a numerical example.

Facility location under demand uncertainty: Response to a large-scale bio-terror attack

2012 ◽  
Vol 46 (1) ◽  
pp. 78-87 ◽  
Author(s):  
Pavankumar Murali ◽  
Fernando Ordóñez ◽  
Maged M. Dessouky
Keyword(s):  
Facility Location ◽  
Large Scale ◽  
Demand Uncertainty ◽  
Terror Attack

Two-Facility Location Problem with Infinite Retrial Queue

2011 ◽  
Vol 2 (3) ◽  
pp. 38-54 ◽  
Author(s):  
Ebrahim Teimoury ◽  
Mohammad Modarres Yazdi ◽  
Iman Ghaleh Khondabi ◽  
Mahdi Fathi
Keyword(s):  
Steady State ◽  
Facility Location ◽  
Demand Uncertainty ◽  
Location Problem ◽  
Retrial Queue ◽  
Facility Location Problem ◽  
Fixed Cost ◽  
Service Demand ◽  
Performance Indexes ◽  
Primary Service

This paper analyzes a two-facility location problem under demand uncertainty. The maximum server for the ith facility is . It is assumed that primary service demand arrivals for the ith facility follow a Poisson process. Each customer chooses one of the facilities with a probability which depends on his or her distance to each facility. The service times are assumed to be exponential and there is no vacation or failure in the system. Both facilities are assumed to be substitutable which means that if a facility has no free server, the other facility is used to fulfill the demand. When there is no idle server in both facilities, each arriving primary demand goes into an orbit of unlimited size. The orbiting demands retry to get service following an exponential distribution. In this paper, the authors give a stability condition of the demand satisfying process, and then obtain the steady-state distribution by applying matrix geometric method in order to calculation of some key performance indexes. By considering the fixed cost of opening a facility and the steady state service costs, the best locations for two facilities are derived. The result is illustrated by a numerical example.

scholarly journals Integrated facility location and capacity planning under uncertainty

2021 ◽  
Vol 40 (5) ◽  
Author(s):  
Isabel Correia ◽  
Teresa Melo
Keyword(s):  
Facility Location ◽  
Capacity Planning ◽  
Demand Uncertainty ◽  
Computational Study ◽  
Minimum Cost ◽  
Planning Horizon ◽  
Planning Under Uncertainty ◽  
Planning Capacity ◽  
The Impact ◽  
Customer Demands

AbstractWe address a multi-period facility location problem with two customer segments having distinct service requirements. While customers in one segment receive preferred service, customers in the other segment accept delayed deliveries as long as lateness does not exceed a pre-specified threshold. The objective is to define a schedule for facility deployment and capacity scalability that satisfies all customer demands at minimum cost. Facilities can have their capacities adjusted over the planning horizon through incrementally increasing or reducing the number of modular units they hold. These two features, capacity expansion and capacity contraction, can help substantially improve the flexibility in responding to demand changes. Future customer demands are assumed to be unknown. We propose two different frameworks for planning capacity decisions and present a two-stage stochastic model for each one of them. While in the first model decisions related to capacity scalability are modeled as first-stage decisions, in the second model, capacity adjustments are deferred to the second stage. We develop the extensive forms of the associated stochastic programs for the case of demand uncertainty being captured by a finite set of scenarios. Additional inequalities are proposed to enhance the original formulations. An extensive computational study with randomly generated instances shows that the proposed enhancements are very useful. Specifically, 97.5% of the instances can be solved to optimality in much shorter computing times. Important insights are also provided into the impact of the two different frameworks for planning capacity adjustments on the facility network configuration and its total cost.

Robust facility location under demand uncertainty and facility disruptions

Omega ◽  
2021 ◽  
pp. 102429
Author(s):  
Chun Cheng ◽  
Yossiri Adulyasak ◽  
Louis-Martin Rousseau
Keyword(s):  
Facility Location ◽  
Demand Uncertainty
Sign in / Sign up

Export Citation Format

Share Document