TY - CHAP

T1 - MIP Modeling of Incremental Connected Facility Location

AU - Arulselvan, Ashwin

AU - Bley, Andreas

AU - Gollowitzer, Stefan

AU - Ljubic, Ivana

AU - Maurer, Olaf

PY - 2011

Y1 - 2011

N2 - We consider the incremental connected facility location problem, in which we are given a set of potential facilities, a set of interconnection nodes, a set of customers with demands, and a planning horizon. For each time period, we have to select a set of facilities to open, a set of customers to be served, the assignment of these customers to the open facilities, and a network that connects the open facilities. Once a customer is served, it must also be served in subsequent periods. Furthermore, in each time period the total demand of all customers served must be at least equal to a given minimum coverage requirement for that period. The objective is to maximize the net present value of the network, which is given by the discounted revenues of serving the customers and by the discounted investments and maintenance costs for the facilities and the network. We study different MIP models for this problem, discuss some valid inequalities to strengthen these formulations, and present a branch and cut algorithm for finding its solution. Finally, we report (preliminary) computational results of our implementation of this algorithm.

AB - We consider the incremental connected facility location problem, in which we are given a set of potential facilities, a set of interconnection nodes, a set of customers with demands, and a planning horizon. For each time period, we have to select a set of facilities to open, a set of customers to be served, the assignment of these customers to the open facilities, and a network that connects the open facilities. Once a customer is served, it must also be served in subsequent periods. Furthermore, in each time period the total demand of all customers served must be at least equal to a given minimum coverage requirement for that period. The objective is to maximize the net present value of the network, which is given by the discounted revenues of serving the customers and by the discounted investments and maintenance costs for the facilities and the network. We study different MIP models for this problem, discuss some valid inequalities to strengthen these formulations, and present a branch and cut algorithm for finding its solution. Finally, we report (preliminary) computational results of our implementation of this algorithm.

KW - facility location

KW - valid inequality

KW - greedy randomize adaptive search procedure

KW - facility location problem

KW - Steiner tree problem (STP)

U2 - 10.1007/978-3-642-21527-8_54

DO - 10.1007/978-3-642-21527-8_54

M3 - Chapter

VL - 6701

T3 - Lecture Notes in Computer Science

SP - 490

EP - 502

BT - Network Optimization

A2 - Pahl, J.

A2 - Reiners , T.

A2 - Voß, S.

PB - Springer

CY - Berlin

T2 - International Conference on Network Optimization - INOC2011

Y2 - 13 June 2011 through 16 June 2011

ER -