A constraint programming model for the scheduling of JIT cross-docking systems with preemption
In this paper, a scheduling problem of minimizing the total of the earliness, tardiness and the number of preemption for the outbound trucks on a cross-dock system is considered. This problem, which is known to be NP-hard, is compatible with the concepts of just-in-time (JIT) production and supply c...
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| Vydáno v: | Journal of intelligent manufacturing Ročník 27; číslo 2; s. 297 - 313 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
Springer US
01.04.2016
Springer Nature B.V |
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| ISSN: | 0956-5515, 1572-8145 |
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| Abstract | In this paper, a scheduling problem of minimizing the total of the earliness, tardiness and the number of preemption for the outbound trucks on a cross-dock system is considered. This problem, which is known to be NP-hard, is compatible with the concepts of just-in-time (JIT) production and supply chain management. A new multi-criteria model, with non-linear terms and integer variables, which cannot be solved efficiently for large sized problems, is proposed. This paper also shows how to map a JIT cross-dock model to a constraint satisfaction problem (CSP) and integer programming (IP). To solve the model for real size applications, a genetic algorithm (GA) is applied. Finally, a computational experiment is carried out to analyze the performances of CSP, GA and IP models with respect to modeling capability, solution quality and time. |
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| AbstractList | In this paper, a scheduling problem of minimizing the total of the earliness, tardiness and the number of preemption for the outbound trucks on a cross-dock system is considered. This problem, which is known to be NP-hard, is compatible with the concepts of just-in-time (JIT) production and supply chain management. A new multi-criteria model, with non-linear terms and integer variables, which cannot be solved efficiently for large sized problems, is proposed. This paper also shows how to map a JIT cross-dock model to a constraint satisfaction problem (CSP) and integer programming (IP). To solve the model for real size applications, a genetic algorithm (GA) is applied. Finally, a computational experiment is carried out to analyze the performances of CSP, GA and IP models with respect to modeling capability, solution quality and time. |
| Author | Fazel Zarandi, M. H. Khorshidian, H. Akbarpour Shirazi, M. |
| Author_xml | – sequence: 1 givenname: M. H. surname: Fazel Zarandi fullname: Fazel Zarandi, M. H. email: zarandi@aut.ac.ir organization: Department of Industrial Engineering, Amirkabir University of Technology – sequence: 2 givenname: H. surname: Khorshidian fullname: Khorshidian, H. organization: Department of Industrial Engineering, Amirkabir University of Technology – sequence: 3 givenname: M. surname: Akbarpour Shirazi fullname: Akbarpour Shirazi, M. organization: Department of Industrial Engineering, Amirkabir University of Technology |
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| CitedBy_id | crossref_primary_10_1007_s10845_014_1014_4 crossref_primary_10_1007_s10878_022_00871_0 crossref_primary_10_1016_j_compind_2016_07_006 crossref_primary_10_1007_s10462_018_9667_6 crossref_primary_10_1016_j_tre_2020_102123 crossref_primary_10_1088_1757_899X_212_1_012020 crossref_primary_10_1080_0305215X_2019_1699919 crossref_primary_10_1016_j_ijpe_2017_09_008 crossref_primary_10_1080_21681015_2020_1772384 crossref_primary_10_1080_00207543_2022_2062580 crossref_primary_10_1080_00207543_2022_2154404 crossref_primary_10_1016_j_cie_2025_111423 crossref_primary_10_1080_08874417_2022_2143455 crossref_primary_10_1080_00207543_2018_1464678 crossref_primary_10_1155_2021_5592122 crossref_primary_10_1016_j_cor_2025_107183 crossref_primary_10_1007_s10878_023_01057_y crossref_primary_10_3390_su11195245 crossref_primary_10_3934_jimo_2025101 crossref_primary_10_1007_s13198_024_02516_3 crossref_primary_10_1007_s10845_015_1156_z crossref_primary_10_1016_j_cor_2023_106386 crossref_primary_10_1016_j_jclepro_2018_12_106 crossref_primary_10_1007_s10845_016_1229_7 crossref_primary_10_1007_s10845_015_1117_6 crossref_primary_10_1155_2021_2026834 crossref_primary_10_1016_j_swevo_2022_101149 crossref_primary_10_1016_j_cie_2016_03_021 crossref_primary_10_1016_j_cie_2019_106134 |
| Cites_doi | 10.1023/A:1024653810491 10.1016/j.cie.2010.08.012 10.1016/j.omega.2009.10.008 10.1016/j.eswa.2011.09.038 10.1007/s10845-008-0125-1 10.1016/j.rcim.2010.04.005 10.1016/S0360-8352(02)00065-7 10.1016/j.ejor.2008.01.008 10.1016/j.ejor.2007.10.051 10.1007/s00170-009-2429-5 10.1016/j.omega.2012.01.005 10.1016/j.ejor.2006.10.047 10.1016/S0377-2217(98)00364-6 10.1007/s10845-010-0427-y 10.1016/j.autcon.2011.04.012 |
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| Keywords | Just-in-time scheduling Preemption Constraint satisfaction problem Genetic algorithm Cross-docking system |
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| SubjectTerms | Advanced manufacturing technologies Business and Management Chains Compatibility Control Docking Experiments Genetic algorithms Integer programming Just in time Logistics Machines Management Manufacturing Mathematical models Mechatronics Multiple criterion Nonlinearity Processes Production Production scheduling Robotics Scheduling Studies Supply chain management Trucks |
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| Title | A constraint programming model for the scheduling of JIT cross-docking systems with preemption |
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