A goal programming model for the optimization of log logistics considering sorting decisions and social objectives
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Date
2022-05
Publication Type
Journal Article
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yes
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Abstract
Log logistics include sorting, processing and transportation of logs from their place of harvest to demand locations. These activities account for a significant portion of the total log procurement costs, therefore, attempts were made in previous studies to optimize some aspects of log logistics. However, operational details, such as sorting decisions, truck compatibility requirements, and social objectives, are often disregarded in the optimization literature. Incorporating these details into the model makes the results more realistic and applicable. To address these gaps, a bi-objective mixed-integer programming model is developed in this paper in order to optimize log logistics. The first objective is to minimize total logistics costs, and the second objective is to provide a balanced workload for trucking contractors. The bi-objective model is solved using the goal programming approach. The model is applied to log logistics of a large Canadian forest company, where trucking contractors use heterogeneous fleet of trucks to carry various log sorts from cut-blocks to sort yards for sorting. The planning horizon is four weeks with daily decisions. The goal programming model generates balanced workloads for the contractors with less than 0.4% increase in total costs compared to the single objective model where only the total cost is minimized.
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published
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Journal / series
Volume
52 (5)
Pages / Article No.
716 - 726
Publisher
Canadian Science Publishing
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Software
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Date collected
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Subject
log logistics; goal programming; bi-objective optimization; social objective; sorting decisions; compatibility requirements; logistique des rondins; programmation des objectifs; optimisation bi-critères; objectif social; décisions de tri; exigences de compatibilité
Organisational unit
09723 - Griess, Verena C. / Griess, Verena C.
02350 - Dep. Umweltsystemwissenschaften / Dep. of Environmental Systems Science