A Location Based Heuristic for General Routing Problems

We present a general framework for modeling routing problems based on formulating them as a traditional location problem called the capacitated concentrator location problem. We apply this framework to two classical routing problems: the capacitated vehicle routing problem and the inventory routing...

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Bibliographic Details
Published in:Operations research Vol. 43; no. 4; pp. 649 - 660
Main Authors: Bramel, Julien, Simchi-Levi, David
Format: Journal Article
Language:English
Published: Linthicum, MD INFORMS 01.07.1995
Operations Research Society of America
Institute for Operations Research and the Management Sciences
Subjects:
Algorithms
analysis of algorithms
Applied sciences
Cost efficiency
Customers
Exact sciences and technology
Fixed costs
Heuristic
Heuristics
integer
Integer programming
Logistics
Operational research and scientific management
Operational research. Management science
Operations research
Optimal solutions
programming
relaxation
Retail stores
Routing
Seed set
Studies
subgradient
suboptimal algorithms
transportation
Transportation costs
Vehicle capacity
vehicle routing
Vehicles
Operating cost
Routing
Capacity of traffic
Algorithm
Modeling
Location problem
Integer programming
Road transportation
Relaxation
Transportation problem
Heuristic method
Numerical simulation
Distribution system
Inventory
Method study
Logistics
ISSN:0030-364X, 1526-5463
Online Access:Get full text
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Summary:We present a general framework for modeling routing problems based on formulating them as a traditional location problem called the capacitated concentrator location problem. We apply this framework to two classical routing problems: the capacitated vehicle routing problem and the inventory routing problem. In the former case, the heuristic is proven to be asymptotically optimal for any distribution of customer demands and locations. Computational experiments show that the heuristic performs well for both problems and, in most cases, outperforms all published heuristics on a set of standard test problems.
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ISSN:0030-364X
1526-5463
DOI:10.1287/opre.43.4.649