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Decision Making in Wood Supply Chain Operations Using Simulation-Based Many-Objective Optimization for Enhancing Delivery Performance and Robustness
Department of Civil and Industrial Engineering, Uppsala University, Sweden ; Skogforsk, The Forestry Research Institute of Sweden, Uppsala, Sweden.ORCID iD: 0009-0005-5953-3121
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Department of Civil and Industrial Engineering, Uppsala University, Sweden. (Virtual Production Development (VPD))ORCID iD: 0000-0003-0111-1776
2026 (English)In: Computers, E-ISSN 2073-431X, Vol. 15, no 1, p. 1-18, article id 70Article in journal (Refereed) Published
Abstract [en]

Wood supply chains are complex, involving many stakeholders, intricate processes, and logistical challenges to ensure the timely and accurate delivery of wood products to customers. Weather-related variations in forest road accessibility further complicate operations. This paper explores the challenges faced by forest managers in targeting many delivery requirements—four or more. To address this, simulation-based optimization, using NSGA-III, a many-objective optimization algorithm, is proposed to simultaneously optimize often conflicting objectives primarily by minimizing delivery lead time, delivery deviations in backlogs, and delivery variation. NSGA-III enables the exploration of a diverse set of Pareto-optimal solutions that show trade-offs across a flexible set of four, or more, delivery objectives. A Discrete Event Simulation model is integrated to evaluate objectives in a complex wood supply chain. The implementation of NSGA-III within the framework allows forestry decision-makers to navigate between different harvest schedules and evaluate how they target a set of preference-based delivery objectives. The simulation can also provide detailed insights into how a specific harvest schedule affects the supply chain when post-processing possible solutions, facilitating decision making. This study shows that NSGA-III could substitute NSGA-II to optimize the wood supply chain for more than three objective functions.

Place, publisher, year, edition, pages
MDPI, 2026. Vol. 15, no 1, p. 1-18, article id 70
Keywords [en]
many-objective optimization, Non-Dominated Sorting Genetic Algorithm-III, Discrete Event Simulation, wood supply chain, delivery performance, harvest scheduling
National Category
Transport Systems and Logistics
Research subject
Virtual Production Development (VPD)
Identifiers
URN: urn:nbn:se:his:diva-26148DOI: 10.3390/computers15010070ISI: 001670153200001Scopus ID: 2-s2.0-105028681508OAI: oai:DiVA.org:his-26148DiVA, id: diva2:2036096
Funder
Swedish Foundation for Strategic Research, FID17-0043
Note

CC BY 4.0

Correspondence: karin.westlund@angstrom.uu.se or karin.westlund@skogforsk.se (K.W.); amos.ng@angstrom.uu.se (A.H.C.N.)

This research was supported by the Swedish Foundation for Strategic Research through the project FID17-0043.

Available from: 2026-02-06 Created: 2026-02-06 Last updated: 2026-02-09Bibliographically approved

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Ng, Amos H. C.

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