The Parallel Machine Scheduling Problem with Different Speeds and Release Times in the Ore Hauling Operation

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Algorithms Pub Date : 2024-08-08 DOI:10.3390/a17080348
Luis Tarazona-Torres, Ciro Amaya, Alvaro Paipilla, Camilo Gomez, David Álvarez-Martínez
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Abstract

Ore hauling operations are crucial within the mining industry as they supply essential minerals to production plants. Conducted with sophisticated and high-cost operational equipment, these operations demand meticulous planning to ensure that production targets are met while optimizing equipment utilization. In this study, we present an algorithm to determine the minimum amount of hauling equipment required to meet the ore transport target. To achieve this, a mathematical model has been developed, considering it as a parallel machine scheduling problem with different speeds and release times, focusing on minimizing both the completion time and the costs associated with equipment use. Additionally, another algorithm was developed to allow the tactical evaluation of these two variables. These procedures and the model contribute significantly to decision-makers by providing a systematic approach to resource allocation, ensuring that loading and hauling equipment are utilized to their fullest potentials while adhering to budgetary constraints and operational schedules. This approach optimizes resource usage and improves operational efficiency, facilitating continuous improvement in mining operations.
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矿石运输作业中不同速度和释放时间的并行机器调度问题
矿石运输作业在采矿业中至关重要,因为它们为生产厂提供重要的矿物。这些作业需要使用精密、高成本的作业设备,因此需要进行细致的规划,以确保在优化设备利用率的同时实现生产目标。在本研究中,我们提出了一种算法,用于确定实现矿石运输目标所需的最小牵引设备数量。为此,我们建立了一个数学模型,将其视为一个具有不同速度和释放时间的并行机器调度问题,重点是最大限度地减少完成时间和与设备使用相关的成本。此外,还开发了另一种算法,以便对这两个变量进行战术评估。这些程序和模型为决策者提供了系统的资源分配方法,确保装载和运输设备在遵守预算限制和作业计划的前提下得到充分利用,从而为决策者做出了重大贡献。这种方法可以优化资源使用,提高运营效率,促进采矿作业的持续改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Algorithms
Algorithms Mathematics-Numerical Analysis
CiteScore
4.10
自引率
4.30%
发文量
394
审稿时长
11 weeks
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