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Algorithms 2018, 11(4), 38; https://doi.org/10.3390/a11040038

Combinatorial GVNS (General Variable Neighborhood Search) Optimization for Dynamic Garbage Collection

1
Department of Informatics, Ionian University, 7 Tsirigoti Square, 49132 Corfu, Greece
2
Department of Applied Informatics, University of Macedonia, 54636 Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Received: 20 November 2017 / Revised: 7 March 2018 / Accepted: 23 March 2018 / Published: 27 March 2018
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Abstract

General variable neighborhood search (GVNS) is a well known and widely used metaheuristic for efficiently solving many NP-hard combinatorial optimization problems. We propose a novel extension of the conventional GVNS. Our approach incorporates ideas and techniques from the field of quantum computation during the shaking phase. The travelling salesman problem (TSP) is a well known NP-hard problem which has broadly been used for modelling many real life routing cases. As a consequence, TSP can be used as a basis for modelling and finding routes via the Global Positioning System (GPS). In this paper, we examine the potential use of this method for the GPS system of garbage trucks. Specifically, we provide a thorough presentation of our method accompanied with extensive computational results. The experimental data accumulated on a plethora of TSP instances, which are shown in a series of figures and tables, allow us to conclude that the novel GVNS algorithm can provide an efficient solution for this type of geographical problem. View Full-Text
Keywords: metaheuristics; VNS; quantum-inspired; optimization; TSP; routing algorithms; GPS application; garbage collection metaheuristics; VNS; quantum-inspired; optimization; TSP; routing algorithms; GPS application; garbage collection
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Papalitsas, C.; Karakostas, P.; Andronikos, T.; Sioutas, S.; Giannakis, K. Combinatorial GVNS (General Variable Neighborhood Search) Optimization for Dynamic Garbage Collection. Algorithms 2018, 11, 38.

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