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Smart Strategies for Project Scheduling: An Adaptive BR-DEH Approach

Xabier A. Martin*, Javier Panadero, Angel A. Juan

*Autor corresponent d’aquest treball

Producció científica: Capítol de llibreCapítolRecercaAvaluat per experts

Resum

In recent years, management of multiple complex projects has become increasingly common among large-scale companies, posing significant challenges for company managers. These projects are often identified by numerous tasks that have precedence relations and share a set of limited resources. The main goal of project scheduling is to minimize the total time required to complete these projects. However, this requires careful consideration of resource allocation, careful scheduling choices, and exact sequencing to maximize efficiency while managing the complex interactions between task dependencies. A novel discrete-event heuristic is presented to solve this project scheduling problem, which is later extended into a probabilistic algorithm using biased-randomization techniques. In addition, an adaptive mechanism was introduced to tune the parameters of the algorithm for optimal scheduling in different problem instances. Computational results demonstrate the effectiveness of our approach, finding high-quality solutions for difficult problem sets in short computational times. This intuitive and efficient approach can empower company managers to efficiently improve operational efficiency, reduce project costs, and ultimately increase their business’s success.
Idioma originalAnglès
Títol de la publicacióDecision Sciences - 2nd Decision Science Alliance International Summer Conference, DSA ISC 2024, Proceedings
EditorsAngel A. Juan, Javier Faulin, David Lopez-Lopez
EditorSpringer Science and Business Media Deutschland GmbH
Pàgines383-393
Nombre de pàgines11
Volum14779
ISBN (electrònic)978-3-031-78241-1
ISBN (imprès)9783031782404
DOIs
Estat de la publicacióPublicada - 1 de gen. 2025

Sèrie de publicacions

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volum14779 LNCS

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