Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
Cyclic transfer algorithms for multivehicle routing and scheduling problems
Operations Research
A tabu search heuristic for the vehicle routing problem
Management Science
Ejection chains, reference structures and alternating path methods for traveling salesman problems
Discrete Applied Mathematics - Special volume: first international colloquium on graphs and optimization (GOI), 1992
A Subpath Ejection Method for the Vehicle Routing Problem
Management Science
Local Search in Combinatorial Optimization
Local Search in Combinatorial Optimization
Tabu Search
An Iterated Dynasearch Algorithm for the Single-Machine Total Weighted Tardiness Scheduling Problem
INFORMS Journal on Computing
A survey of very large-scale neighborhood search techniques
Discrete Applied Mathematics
Performance of Various Computers Using Standard Linear Equations Software
Performance of Various Computers Using Standard Linear Equations Software
New neighborhood search algorithms based on exponentially large neighborhoods
New neighborhood search algorithms based on exponentially large neighborhoods
The Granular Tabu Search and Its Application to the Vehicle-Routing Problem
INFORMS Journal on Computing
Elements of discrete mathematics (McGraw-Hill computer science series)
Elements of discrete mathematics (McGraw-Hill computer science series)
An efficient variable neighborhood search heuristic for very large scale vehicle routing problems
Computers and Operations Research
Iterated variable neighborhood descent algorithm for the capacitated vehicle routing problem
Expert Systems with Applications: An International Journal
Fifty Years of Vehicle Routing
Transportation Science
Journal of Intelligent Manufacturing
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This paper discusses neighborhood search algorithms where the size of the neighborhood is "very large" with respect to the size of the input data. We concentrate on such a very large scale neighborhood (VLSN) search technique based on compounding independent moves (CIM) such as 2-opts, swaps, and insertions. We present a systematic way of creating and searching CIM neighborhoods for routing problems with side constraints. For such problems, the exact search of the CIM neighborhood becomes NP-hard. We introduce a multi-label shortest path algorithm for searching these neighborhoods heuristically. Results of a computational study on the vehicle routing problem with capacity and distance restrictions shows that CIM algorithms are very competitive approaches for solving vehicle routing problems. Overall, the solutions generated by the CIM algorithm have the best performance among the current solution methodologies in terms of percentage deviation from the best-known solutions for large-scale capacitated VRP instances.