Improved Multi-Objective Beluga Whale Optimization Algorithm for Truck Scheduling in Open-Pit Mines

Big data and artificial intelligence have promoted mining innovation and sustainable development, and the transportation used in open-pit mining has increasingly incorporated unmanned driving, real-time information sharing, and intelligent algorithm applications. However, the traditional manual sche...

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Vydáno v:Sustainability Ročník 16; číslo 16; s. 6939
Hlavní autoři: Zhang, Pengchao, Liu, Xiang, Yi, Zebang, He, Qiuzhi
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.08.2024
Témata:
Algorithms
Artificial intelligence
Automobile safety
Carbon
Case studies
Efficiency
Environmental protection
Equipment and supplies
Genetic algorithms
Integer programming
Linear programming
Management
Mathematical optimization
Mineral industry
Mines
Mining
Mining industry
Operating costs
Optimization algorithms
Scheduling
Scheduling (Management)
Technology application
Traffic congestion
Trucks
Working hours
China
ISSN:2071-1050, 2071-1050
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Abstract Big data and artificial intelligence have promoted mining innovation and sustainable development, and the transportation used in open-pit mining has increasingly incorporated unmanned driving, real-time information sharing, and intelligent algorithm applications. However, the traditional manual scheduling used for mining transportation often prioritizes output over efficiency and quality, resulting in high operational expenses, traffic jams, and long lines. In this study, a novel scheduling model with multi-objective optimization was created to overcome these problems. Production, demand, ore grade, and vehicle count were the model’s constraints. The optimization goals were to minimize the shipping cost, total waiting time, and ore grade deviation. An enhanced multi-objective beluga whale optimization (IMOBWO) algorithm was implemented in the model. The algorithm’s superior performance was demonstrated in ten test functions, as well as the IEEE 30-bus system. It was enhanced by optimizing the population initialization, improving the adaptive factor, and adding dynamic domain perturbation. The case analysis showed that, in comparison to the other three conventional multi-objective algorithms, IMOBWO reduced the shipping cost from 7.65 to 0.84%, the total waiting time from 35.7 to 7.54%, and the ore grade deviation from 14.8 to 3.73%. The implementation of this algorithm for truck scheduling in open-pit mines increased operational efficiency, decreased operating costs, and advanced intelligent mine construction and transportation systems. These factors play a significant role in the safety, profitability, and sustainability of open-pit mines.
AbstractList Big data and artificial intelligence have promoted mining innovation and sustainable development, and the transportation used in open-pit mining has increasingly incorporated unmanned driving, real-time information sharing, and intelligent algorithm applications. However, the traditional manual scheduling used for mining transportation often prioritizes output over efficiency and quality, resulting in high operational expenses, traffic jams, and long lines. In this study, a novel scheduling model with multi-objective optimization was created to overcome these problems. Production, demand, ore grade, and vehicle count were the model’s constraints. The optimization goals were to minimize the shipping cost, total waiting time, and ore grade deviation. An enhanced multi-objective beluga whale optimization (IMOBWO) algorithm was implemented in the model. The algorithm’s superior performance was demonstrated in ten test functions, as well as the IEEE 30-bus system. It was enhanced by optimizing the population initialization, improving the adaptive factor, and adding dynamic domain perturbation. The case analysis showed that, in comparison to the other three conventional multi-objective algorithms, IMOBWO reduced the shipping cost from 7.65 to 0.84%, the total waiting time from 35.7 to 7.54%, and the ore grade deviation from 14.8 to 3.73%. The implementation of this algorithm for truck scheduling in open-pit mines increased operational efficiency, decreased operating costs, and advanced intelligent mine construction and transportation systems. These factors play a significant role in the safety, profitability, and sustainability of open-pit mines.
Audience Academic
Author Yi, Zebang
Liu, Xiang
Zhang, Pengchao
He, Qiuzhi
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Cites_doi 10.1080/17480930.2021.1996983
10.1109/TEVC.2007.913109
10.1007/978-3-030-84315-1_4
10.1016/j.ejor.2017.03.081
10.1080/09208119408964750
10.1016/j.ejor.2019.01.008
10.1016/j.jclepro.2020.125228
10.1016/j.ijmst.2013.01.017
10.1109/TSG.2022.3203404
10.1016/j.knosys.2022.109215
10.21528/lnlm-vol17-no2-art5
10.1016/j.jsm.2017.07.001
10.1016/j.eswa.2023.122970
10.3390/su15043399
10.1016/j.resconrec.2022.106664
10.1109/ICCSI55536.2022.9970696
10.3390/su14116933
10.1016/j.asej.2021.01.035
10.1016/0167-9031(90)90543-2
10.1016/j.chaos.2007.10.049
10.1076/ijsm.16.1.59.3408
10.2478/rtuect-2020-0019
10.1080/13895260500128914
10.1109/TLA.2016.7459617
10.1016/j.ejor.2010.05.037
10.1016/j.endm.2012.10.031
10.1109/ACCESS.2020.3011109
10.1016/j.eswa.2023.121406
10.1007/s11081-022-09780-x
10.1016/j.rser.2023.113942
10.1142/S0217595910002727
10.1016/j.enbuild.2024.113942
10.1016/j.resourpol.2022.102727
10.3390/electronics12183793
10.1142/S0950609898000092
10.1016/j.resourpol.2021.102522
10.1016/j.ssci.2021.105438
10.1016/j.trc.2023.104080
10.1016/j.ejor.2010.05.031
10.1109/TIV.2024.3365997
10.1109/SGES51519.2020.00034
10.1162/106365600568202
10.1080/09208119708944093
10.1016/j.eswa.2015.10.039
10.1016/j.aej.2023.04.002
10.1080/17480930.2015.1115589
10.1080/17480930.2017.1336607
10.1007/s42243-023-01173-3
10.1179/1743286310Y.0000000001
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References ref_50
Wang (ref_13) 2024; 189
Hassan (ref_42) 2023; 72
Temeng (ref_31) 1997; 11
ref_12
ref_11
Temeng (ref_27) 1998; 7
Alarie (ref_19) 2002; 16
Vergara (ref_49) 2023; 14
Li (ref_41) 2024; 3
Mena (ref_14) 2013; 23
Ismail (ref_6) 2021; 143
Mendes (ref_36) 2016; 14
Munirathinam (ref_18) 1994; 8
Islam (ref_52) 2021; 12
(ref_4) 2019; 33
Shamsi (ref_20) 2022; 36
Rehman (ref_32) 2010; 27
Nebro (ref_46) 2008; 12
Patterson (ref_29) 2017; 262
Purhamadani (ref_1) 2021; 291
Nehring (ref_23) 2010; 119
Coelho (ref_35) 2012; 39
Li (ref_43) 2024; 307
Li (ref_39) 2024; 237
Kanso (ref_45) 2009; 40
Afrapoli (ref_25) 2019; 276
Xing (ref_44) 2024; 244
Chen (ref_9) 2024; 9
ref_30
Kasap (ref_7) 2017; 16
Zhong (ref_38) 2022; 251
Huo (ref_17) 2023; 188
Choi (ref_26) 2022; 75
Noriega (ref_10) 2022; 77
Mohtasham (ref_21) 2023; 24
Kuzmin (ref_2) 2020; 24
Topal (ref_28) 2010; 207
Zhang (ref_15) 2023; 150
ref_47
Li (ref_34) 1990; 10
Alexandre (ref_37) 2019; 17
Santelices (ref_33) 2017; 31
Mirjalili (ref_51) 2016; 47
ref_3
Zitzler (ref_48) 2000; 8
Zhang (ref_22) 2020; 8
Li (ref_40) 2024; 31
ref_8
Ta (ref_16) 2005; 19
ref_5
Souza (ref_24) 2010; 207
References_xml – volume: 36
  start-page: 142
  year: 2022
  ident: ref_20
  article-title: Optimisation of open-pit mine production scheduling considering optimum transportation system between truck haulage and semi-mobile in-pit crushing and conveying
  publication-title: Int. J. Min. Reclam. Environ.
  doi: 10.1080/17480930.2021.1996983
– volume: 12
  start-page: 439
  year: 2008
  ident: ref_46
  article-title: AbYSS: Adapting Scatter Search to Multiobjective Optimization
  publication-title: IEEE Trans. Evol. Comput.
  doi: 10.1109/TEVC.2007.913109
– ident: ref_11
  doi: 10.1007/978-3-030-84315-1_4
– ident: ref_5
– volume: 262
  start-page: 759
  year: 2017
  ident: ref_29
  article-title: Energy efficient scheduling of open-pit coal mine trucks
  publication-title: Eur. J. Oper. Res.
  doi: 10.1016/j.ejor.2017.03.081
– volume: 3
  start-page: 32
  year: 2024
  ident: ref_41
  article-title: Multi-objective optimization design of anti-roll torsion bar using improved beluga whale optimization algorithm
  publication-title: Railw. Sci.
– volume: 8
  start-page: 1
  year: 1994
  ident: ref_18
  article-title: A review of computer-based truck dispatching strategies for surface mining operations
  publication-title: Int. J. Surf. Min. Reclam. Environ.
  doi: 10.1080/09208119408964750
– volume: 276
  start-page: 331
  year: 2019
  ident: ref_25
  article-title: A multiple objective transportation problem approach to dynamic truck dispatching in surface mines
  publication-title: Eur. J. Oper. Res.
  doi: 10.1016/j.ejor.2019.01.008
– volume: 291
  start-page: 125228
  year: 2021
  ident: ref_1
  article-title: Energy consumption in open-pit mining operations relying on reduced energy consumption for haulage using in-pit crusher systems
  publication-title: J. Clean. Prod.
  doi: 10.1016/j.jclepro.2020.125228
– volume: 23
  start-page: 113
  year: 2013
  ident: ref_14
  article-title: Availability-based simulation and optimization modeling framework for open-pit mine truck allocation under dynamic constraints
  publication-title: Int. J. Min. Sci. Technol.
  doi: 10.1016/j.ijmst.2013.01.017
– volume: 14
  start-page: 1249
  year: 2023
  ident: ref_49
  article-title: Critical Data Visualization to Enhance Protection Schemes for State Estimation
  publication-title: IEEE Trans. Smart Grid
  doi: 10.1109/TSG.2022.3203404
– volume: 251
  start-page: 109215
  year: 2022
  ident: ref_38
  article-title: Beluga whale optimization: A novel nature-inspired metaheuristic algorithm
  publication-title: Knowl. Based Syst.
  doi: 10.1016/j.knosys.2022.109215
– volume: 17
  start-page: 53
  year: 2019
  ident: ref_37
  article-title: Multi-objective evolutionary algorithms for the truck dispatch problem in open-pit mining operations
  publication-title: Learn. Nonlinear Models
  doi: 10.21528/lnlm-vol17-no2-art5
– volume: 16
  start-page: 38
  year: 2017
  ident: ref_7
  article-title: Risk assessment of occupational groups working in open pit mining: Analytic Hierarchy Process
  publication-title: J. Sustain. Min.
  doi: 10.1016/j.jsm.2017.07.001
– volume: 244
  start-page: 122970
  year: 2024
  ident: ref_44
  article-title: A novel multivariate combined power load forecasting system based on feature selection and multi-objective intelligent optimization
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2023.122970
– ident: ref_30
  doi: 10.3390/su15043399
– volume: 188
  start-page: 106664
  year: 2023
  ident: ref_17
  article-title: Reinforcement Learning-Based Fleet Dispatching for Greenhouse Gas Emission Reduction in Open-Pit Mining Operations
  publication-title: Resour. Conserv. Recycl.
  doi: 10.1016/j.resconrec.2022.106664
– ident: ref_8
  doi: 10.1109/ICCSI55536.2022.9970696
– ident: ref_50
  doi: 10.3390/su14116933
– volume: 12
  start-page: 3677
  year: 2021
  ident: ref_52
  article-title: Optimized controller design for islanded microgrid using non-dominated sorting whale optimization algorithm (NSWOA)
  publication-title: Ain Shams Eng. J.
  doi: 10.1016/j.asej.2021.01.035
– volume: 10
  start-page: 337
  year: 1990
  ident: ref_34
  article-title: A methodology for the optimum control of shovel and truck operations in open-pit mining
  publication-title: Min. Sci. Technol.
  doi: 10.1016/0167-9031(90)90543-2
– volume: 40
  start-page: 2557
  year: 2009
  ident: ref_45
  article-title: Logistic chaotic maps for binary numbers generations
  publication-title: Chaos Solitons Fractals
  doi: 10.1016/j.chaos.2007.10.049
– volume: 16
  start-page: 59
  year: 2002
  ident: ref_19
  article-title: Overview of solution strategies used in truck dispatching systems for open pit mines
  publication-title: Int. J. Surf. Min. Reclam. Environ.
  doi: 10.1076/ijsm.16.1.59.3408
– volume: 24
  start-page: 341
  year: 2020
  ident: ref_2
  article-title: Development of a New Environmentally-Friendly Technology for Transportation of Mined Rock in the Opencast Mining
  publication-title: Environ. Clim. Technol.
  doi: 10.2478/rtuect-2020-0019
– volume: 19
  start-page: 162
  year: 2005
  ident: ref_16
  article-title: A stochastic optimization approach to mine truck allocation
  publication-title: Int. J. Surf. Min. Reclam. Environ.
  doi: 10.1080/13895260500128914
– volume: 14
  start-page: 1329
  year: 2016
  ident: ref_36
  article-title: A Hybrid Multiobjective Evolutionary Algorithm for Truck Dispatching in Open-Pit-Mining
  publication-title: IEEE Lat. Am. Trans.
  doi: 10.1109/TLA.2016.7459617
– volume: 207
  start-page: 1065
  year: 2010
  ident: ref_28
  article-title: A new MIP model for mine equipment scheduling by minimizing maintenance cost
  publication-title: Eur. J. Oper. Res.
  doi: 10.1016/j.ejor.2010.05.037
– volume: 39
  start-page: 233
  year: 2012
  ident: ref_35
  article-title: Multi-objective approaches for the open-pit mining operational planning problem
  publication-title: Electron. Notes Discret. Math.
  doi: 10.1016/j.endm.2012.10.031
– volume: 8
  start-page: 135524
  year: 2020
  ident: ref_22
  article-title: An Unmanned Intelligent Transportation Scheduling System for Open-Pit Mine Vehicles Based on 5G and Big Data
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2020.3011109
– volume: 237
  start-page: 121406
  year: 2024
  ident: ref_39
  article-title: Multi-objective distributed generation hierarchical optimal planning in distribution network: Improved beluga whale optimization algorithm
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2023.121406
– volume: 24
  start-page: 2449
  year: 2023
  ident: ref_21
  article-title: An optimization model for the real-time truck dispatching problem in open-pit mining operations
  publication-title: Optim. Eng.
  doi: 10.1007/s11081-022-09780-x
– volume: 189
  start-page: 113942
  year: 2024
  ident: ref_13
  article-title: Comprehensive overview: Fleet management drives green and climate-smart open pit mine
  publication-title: Renew. Sustain. Energy Rev.
  doi: 10.1016/j.rser.2023.113942
– volume: 27
  start-page: 315
  year: 2010
  ident: ref_32
  article-title: A mixed-integer linear programming (MILP) model for short-range production scheduling of cement quarry operations
  publication-title: Asia-Pac. J. Oper. Res.
  doi: 10.1142/S0217595910002727
– ident: ref_47
– volume: 307
  start-page: 113942
  year: 2024
  ident: ref_43
  article-title: Optimal loading distribution of chillers based on an improved beluga whale optimization for reducing energy consumption
  publication-title: Energy Build.
  doi: 10.1016/j.enbuild.2024.113942
– volume: 77
  start-page: 102727
  year: 2022
  ident: ref_10
  article-title: A systematic review of artificial intelligence and data-driven approaches in strategic open-pit mine planning
  publication-title: Resour. Policy
  doi: 10.1016/j.resourpol.2022.102727
– ident: ref_3
  doi: 10.3390/electronics12183793
– volume: 7
  start-page: 59
  year: 1998
  ident: ref_27
  article-title: A nonpreemptive goal programming approach to truck dispatching in open pit mines
  publication-title: Miner. Resour. Eng.
  doi: 10.1142/S0950609898000092
– volume: 75
  start-page: 102522
  year: 2022
  ident: ref_26
  article-title: Optimization of haulage-truck system performance for ore production in open-pit mines using big data and machine learning-based methods
  publication-title: Resour. Policy
  doi: 10.1016/j.resourpol.2021.102522
– volume: 143
  start-page: 105438
  year: 2021
  ident: ref_6
  article-title: Research trends in mining accidents study: A systematic literature review
  publication-title: Saf. Sci.
  doi: 10.1016/j.ssci.2021.105438
– volume: 150
  start-page: 104080
  year: 2023
  ident: ref_15
  article-title: A dynamic dispatching problem for autonomous mine trucks in open-pit mines considering endogenous congestion
  publication-title: Transp. Res. Part C: Emerg. Technol.
  doi: 10.1016/j.trc.2023.104080
– volume: 207
  start-page: 1041
  year: 2010
  ident: ref_24
  article-title: A hybrid heuristic algorithm for the open-pit-mining operational planning problem
  publication-title: Eur. J. Oper. Res.
  doi: 10.1016/j.ejor.2010.05.031
– volume: 9
  start-page: 4383
  year: 2024
  ident: ref_9
  article-title: Smart Mining With Autonomous Driving in Industry 5.0: Architectures, Platforms, Operating Systems, Foundation Models, and Applications
  publication-title: IEEE Trans. Intell. Veh.
  doi: 10.1109/TIV.2024.3365997
– ident: ref_12
  doi: 10.1109/SGES51519.2020.00034
– volume: 8
  start-page: 173
  year: 2000
  ident: ref_48
  article-title: Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
  publication-title: Evol. Comput.
  doi: 10.1162/106365600568202
– volume: 11
  start-page: 203
  year: 1997
  ident: ref_31
  article-title: Real-time truck dispatching using a transportation algorithm
  publication-title: Int. J. Surf. Min. Reclam. Environ.
  doi: 10.1080/09208119708944093
– volume: 47
  start-page: 106
  year: 2016
  ident: ref_51
  article-title: Multi-objective grey wolf optimizer: A novel algorithm for multi-criterion optimization
  publication-title: Expert Syst. Appl.
  doi: 10.1016/j.eswa.2015.10.039
– volume: 72
  start-page: 573
  year: 2023
  ident: ref_42
  article-title: Economic load dispatch solution of large-scale power systems using an enhanced beluga whale optimizer
  publication-title: Alex. Eng. J.
  doi: 10.1016/j.aej.2023.04.002
– volume: 31
  start-page: 52
  year: 2017
  ident: ref_33
  article-title: Integrating mining loading and hauling equipment selection and replacement decisions using stochastic linear programming
  publication-title: Int. J. Min. Reclam. Environ.
  doi: 10.1080/17480930.2015.1115589
– volume: 33
  start-page: 42
  year: 2019
  ident: ref_4
  article-title: Mining fleet management systems: A review of models and algorithms
  publication-title: Int. J. Min. Reclam. Environ.
  doi: 10.1080/17480930.2017.1336607
– volume: 31
  start-page: 1597
  year: 2024
  ident: ref_40
  article-title: Optimal proportioning of iron ore in sintering process based on improved multi-objective beluga whale optimisation algorithm
  publication-title: J. Iron Steel Res. Int.
  doi: 10.1007/s42243-023-01173-3
– volume: 119
  start-page: 212
  year: 2010
  ident: ref_23
  article-title: Dynamic short term production scheduling and machine allocation in underground mining using mathematical programming
  publication-title: Min. Technol.
  doi: 10.1179/1743286310Y.0000000001
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Snippet Big data and artificial intelligence have promoted mining innovation and sustainable development, and the transportation used in open-pit mining has...
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SubjectTerms Algorithms
Artificial intelligence
Automobile safety
Carbon
Case studies
Efficiency
Environmental protection
Equipment and supplies
Genetic algorithms
Integer programming
Linear programming
Management
Mathematical optimization
Mineral industry
Mines
Mining
Mining industry
Operating costs
Optimization algorithms
Scheduling
Scheduling (Management)
Technology application
Traffic congestion
Trucks
Working hours
Title Improved Multi-Objective Beluga Whale Optimization Algorithm for Truck Scheduling in Open-Pit Mines
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