A biased-randomized iterated local search for the vehicle routing problem with optional backhauls

The vehicle routing problem with backhauls integrates decisions on product delivery with decisions on the collection of returnable items. In this paper, we analyze a scenario in which collection of items is optional—but subject to a penalty cost. Both transportation costs and penalties associated wi...

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Veröffentlicht in:TOP 2021-07, Vol.29 (2), p.387-416
Hauptverfasser: Londoño, Julio C., Tordecilla, Rafael D., Martins, Leandro do C., Juan, Angel A.
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Tordecilla, Rafael D.
Martins, Leandro do C.
Juan, Angel A.
description The vehicle routing problem with backhauls integrates decisions on product delivery with decisions on the collection of returnable items. In this paper, we analyze a scenario in which collection of items is optional—but subject to a penalty cost. Both transportation costs and penalties associated with non-collecting decisions are considered. A mixed-integer linear model is proposed and solved for small instances. Also, a metaheuristic algorithm combining biased randomization techniques with iterated local search is introduced for larger instances. Our approach yields cost savings and is competitive when compared to other state-of-the-art approaches.
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subjects Algorithms
Business and Management
Cost control
Decisions
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Finance
Heuristic methods
Industrial and Production Engineering
Insurance
Management
Mixed integer
Operating costs
Operations Research/Decision Theory
Optimization
Original Paper
Randomization
Route planning
Statistics for Business
Vehicle routing
title A biased-randomized iterated local search for the vehicle routing problem with optional backhauls
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