EURO 2024 Copenhagen
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3278. Hybrid Randomised and Greedy Technique as a Novel Approach to Solve the Open Vehicle Routing Problem (OVRP)

Invited abstract in session WD-64: Heuristics for Vehicle Routing 2, stream VeRoLog - Vehicle Routing and Logistics.

Wednesday, 14:30-16:00
Room: S16 (building: 101)

Authors (first author is the speaker)

1. Abdullah Almouhanna
Department of Mathematics, University of Portsmouth
2. Hassana Abdullahi
Cardiff School of Management, Cardiff Metropolitan University
3. Angel A. Juan
ValgrAI | ICSO Analytics | CIGIP, Universitat Politècnica de València

Abstract

The Open Vehicle Routing Problem (OVRP) is a complex combinatorial optimization challenge with numerous real-world applications in transportation, logistics, and urban planning.
The OVRP differs from the Vehicle Routing Problem (VRP) because the vehicles either are not required to return to the depot, or if they are to so do by revisiting the customers in the reverse order.
The OVRP is faced by a company which either does not own a vehicle fleet at all, or its vehicle fleet is inappropriate or inadequate to satisfy the demand of its customers.
Our approach is based on combination of the Iterated Greedy (IG) with biased randomization technique.
The IG has been developed by to solve the Permutation Flowshop Scheduling Problem (PFSP) in order to minimise makespan. It is reasonably simple to implement and parameter free.
One of our aim of choosing this method is that, the IG has been applied successfully for some Combinatorial Problems specifically and has been proven to generate high quality solutions. Despite the proven impressive performance of IG, it has not been applied in the OVRP.
Biased randomisation technique refers to the utilisation of pseudo-random numbers to generate random outcomes throughout the solution search. By randomizing some steps in a deterministic heuristic, it is transformed into a probabilistic procedure. Then, it can be run multiple times – either in sequential or parallel mode – in order to obtain different outcomes or solutions.

Keywords

Status: accepted

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