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Related Experiment Video

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Orienteering as a Tool for Cognitive Research: An Implementation Guide

Orienteering as a Tool for Cognitive Research: An Implementation Guide

Published on: November 29, 2024

Iterated local search algorithm for solving the orienteering problem with soft time windows.

Brahim Aghezzaf¹, Hassan El Fahim¹

¹Laboratoire Informatique et Aide à la Décision (LIAD), Département de Mathématiques et Informatique, Faculté des Sciences Aïn Chock, Université Hassan II de Casablanca, Km 8 Route d'El Jadida, 5366 Maarif, 20100 Casablanca, Morocco.

|November 1, 2016

Summary

This study explores the orienteering problem with time windows (OPTW) and introduces a soft time window variant (OPSTW). Relaxing time windows in OPSTW improves collected profit compared to OPTW.

Keywords:

Combinatorial optimization Iterated local search Orienteering problem Soft time window Variable neighborhood search

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Area of Science:

Operations Research
Combinatorial Optimization
Logistics Management

Background:

The orienteering problem with time windows (OPTW) is a complex routing problem.
Strict time windows in OPTW can limit achievable profit.
Relaxing time windows is a potential strategy to enhance collection efficiency.

Purpose of the Study:

To investigate the impact of relaxing time windows on profit in the orienteering problem.
To introduce and analyze the orienteering problem with soft time windows (OPSTW).
To develop and evaluate a heuristic approach for solving the OPSTW.

Main Methods:

The study introduces a late service relaxation for soft time windows, with linear penalties.
A hybrid iterated local search heuristic is employed to solve the OPSTW.
The proposed method is tested on existing OPTW instances and newly generated OPSTW instances.

Main Results:

The hybrid iterated local search achieved promising solutions on OPTW instances, including a new best-known solution.
The OPSTW formulation demonstrated higher collected profit compared to the standard OPTW.
The heuristic approach effectively handles the relaxed time window constraints.

Conclusions:

Relaxing time windows in the orienteering problem, specifically through soft time windows with linear penalties, can lead to increased profit.
The developed hybrid iterated local search is an effective heuristic for the OPSTW.
This research provides valuable insights into optimizing routing problems with flexible time constraints.