Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/733
Title: Variable neighborhood search-based solution methods for the pollution location-inventory-routing problem
Authors: Karakostas, Panagiotis
Sifaleras, Angelo
Georgiadis, Michael C.
Type: Article
Subjects: FRASCATI::Natural sciences::Mathematics::Applied Mathematics
FRASCATI::Natural sciences::Computer and information sciences
Keywords: Variable Neighborhood Search
Facility Location
Vehicle Routing Problem
Inventory Management
Issue Date: 2020
Publisher: Springer
Source: Optimization Letters
Abstract: This work presents efficient solution approaches for a new complex NP-hard combinatorial optimization problem, the Pollution Location Inventory Routing problem (PLIRP), which considers both economic and environmental issues. A mixed-integer linear programming (MILP) model is proposed and first, small problem instances are solved using the CPLEX solver. Due to its computational complexity, General Variable Neighborhood Search (GVNS)-based metaheuristic algorithms are developed for the solution of medium and large instances. The proposed approaches are tested on 30 new randomly generated PLIRP instances. Parameter estimation has been performed for determining the most suitable perturbation strength. An extended numerical analysis illustrates the effectiveness and efficiency of the underlying methods, leading to high-quality solutions with limited computational effort. Furthermore, the impact of holding cost variations to the total cost is studied.
URI: https://doi.org/10.1007/s11590-020-01630-y
https://ruomo.lib.uom.gr/handle/7000/733
ISSN: 1862-4472
1862-4480
Other Identifiers: 10.1007/s11590-020-01630-y
Appears in Collections:Department of Applied Informatics

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