Truck scheduling in multi-door cross docking terminal by modified particle swarm optimization
•A mathematical model for truck scheduling in a multi-door cross docking is shown.•The GLNPSO is proposed with particular encoding and decoding schemes.•GLNPSO generates high quality solutions with fast convergence. In today’s distribution environment, one of the main strategies is to minimize cost...
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| Vydané v: | Computers & industrial engineering Ročník 113; s. 793 - 802 |
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| Jazyk: | English |
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Elsevier Ltd
01.11.2017
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| ISSN: | 0360-8352, 1879-0550 |
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| Abstract | •A mathematical model for truck scheduling in a multi-door cross docking is shown.•The GLNPSO is proposed with particular encoding and decoding schemes.•GLNPSO generates high quality solutions with fast convergence.
In today’s distribution environment, one of the main strategies is to minimize cost by reducing inventory and timely shipments. Cross docking is a logistic management strategy in which products delivered to a distribution center by inbound trucks are immediately loaded to outbound trucks with minimum handling and storage time so that the total cost can be reduced. In a multi-door cross docking terminal, one of the most important operational management problems is the truck scheduling problem which is decomposed to the assignment of trucks to dock doors and the sequence of all inbound and outbound trucks. In this paper, a mathematical model of mixed integer programming for door assigning and truck sequencing in a multi-door cross docking system is presented. The objective of the model is to minimize total operational time or makespan. Then, the modified particle swarm optimization, so called GLNPSO, is proposed with particular encoding and decoding schemes for solving the truck scheduling problem in a multi-door cross docking system. The performances of GLNPSO are evaluated and compared the results with those obtained from the original PSO. The experimental results show that the GLNPSO is capable of finding high quality solutions with fast convergence. |
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| AbstractList | •A mathematical model for truck scheduling in a multi-door cross docking is shown.•The GLNPSO is proposed with particular encoding and decoding schemes.•GLNPSO generates high quality solutions with fast convergence.
In today’s distribution environment, one of the main strategies is to minimize cost by reducing inventory and timely shipments. Cross docking is a logistic management strategy in which products delivered to a distribution center by inbound trucks are immediately loaded to outbound trucks with minimum handling and storage time so that the total cost can be reduced. In a multi-door cross docking terminal, one of the most important operational management problems is the truck scheduling problem which is decomposed to the assignment of trucks to dock doors and the sequence of all inbound and outbound trucks. In this paper, a mathematical model of mixed integer programming for door assigning and truck sequencing in a multi-door cross docking system is presented. The objective of the model is to minimize total operational time or makespan. Then, the modified particle swarm optimization, so called GLNPSO, is proposed with particular encoding and decoding schemes for solving the truck scheduling problem in a multi-door cross docking system. The performances of GLNPSO are evaluated and compared the results with those obtained from the original PSO. The experimental results show that the GLNPSO is capable of finding high quality solutions with fast convergence. |
| Author | Wisittipanich, Warisa Hengmeechai, Piya |
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| Cites_doi | 10.1016/j.cie.2015.12.005 10.1016/j.omega.2012.01.005 10.1016/j.ejor.2007.10.051 10.1080/17509653.2011.10671149 10.1016/j.cie.2008.07.021 10.1016/j.cor.2012.01.002 10.1016/j.omega.2009.10.008 10.1007/s00170-009-2429-5 10.1016/j.eswa.2013.04.019 10.1016/j.cie.2014.05.009 10.1016/j.eswa.2010.07.130 10.1016/j.cie.2013.09.024 10.1016/j.cor.2008.07.003 10.1109/ICNC.2007.453 10.1504/IJOR.2009.026534 10.1016/j.ejor.2006.10.047 10.1016/j.cie.2015.11.006 10.1007/s00291-008-0139-2 10.1016/j.cie.2014.03.002 10.1109/ICNN.1995.488968 10.1016/j.cie.2015.09.008 10.1504/IJOR.2009.023535 |
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| References | Zhang, Shao, Li, Gao (b0115) 2009; 56 (pp. 799–803). Haikou. (pp. 1942–1948). Perth, WA. Keshtzaria, Naderib, Mehdizadehc (b0045) 2016; 91 Maknoon, Kone, Baptiste (b0060) 2014; 72 Pratchayaboriak, Kachitvichyanukul (b0085) 2011; 6 Shakeri, Low, Turner, Lee (b0090) 2012; 39 Arabani, Ghomi, Zandieh (b0005) 2010; 49 Boysen, Fliedner, Scholl (b0025) 2010; 32 Pongchairerks, Kachitvichyanukul (b0080) 2009; 4 Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. In Chen, Song (b0035) 2009; 36 Shi, Eberhart (b9005) 1998 Mansooreh, Reza, Bahman (b0065) 2014; 74 Van Belle, Valckenaers, Vanden Berghe, Cattrysse (b0105) 2013; 66 Mohtashami (b0070) 2015; 90 Chen, Lee (b0030) 2009; 193 Liu, Z. (2007). Investigation of particle swarm optimization for job shop scheduling problem. In Arabani, Ghomi, Zandieh (b0010) 2011; 38 Pongchairerks, Kachitvichyanukul (b0075) 2009; 6 Boysen, Fliedner (b0020) 2010; 38 Kuo (b0050) 2013; 40 Tootkaleh, Ghomi, Sajadieh (b0095) 2016; 92 Van Belle, Valckenaers, Cattrysse (b0100) 2012; 40 Yu, Egbelu (b0110) 2008; 184 Boysen (10.1016/j.cie.2017.01.004_b0025) 2010; 32 Arabani (10.1016/j.cie.2017.01.004_b0005) 2010; 49 Mansooreh (10.1016/j.cie.2017.01.004_b0065) 2014; 74 Pratchayaboriak (10.1016/j.cie.2017.01.004_b0085) 2011; 6 10.1016/j.cie.2017.01.004_b0040 Kuo (10.1016/j.cie.2017.01.004_b0050) 2013; 40 Tootkaleh (10.1016/j.cie.2017.01.004_b0095) 2016; 92 Yu (10.1016/j.cie.2017.01.004_b0110) 2008; 184 10.1016/j.cie.2017.01.004_b0055 Maknoon (10.1016/j.cie.2017.01.004_b0060) 2014; 72 Van Belle (10.1016/j.cie.2017.01.004_b0105) 2013; 66 Keshtzaria (10.1016/j.cie.2017.01.004_b0045) 2016; 91 Mohtashami (10.1016/j.cie.2017.01.004_b0070) 2015; 90 Zhang (10.1016/j.cie.2017.01.004_b0115) 2009; 56 Shakeri (10.1016/j.cie.2017.01.004_b0090) 2012; 39 Chen (10.1016/j.cie.2017.01.004_b0035) 2009; 36 Arabani (10.1016/j.cie.2017.01.004_b0010) 2011; 38 Pongchairerks (10.1016/j.cie.2017.01.004_b0075) 2009; 6 Boysen (10.1016/j.cie.2017.01.004_b0020) 2010; 38 Chen (10.1016/j.cie.2017.01.004_b0030) 2009; 193 Shi (10.1016/j.cie.2017.01.004_b9005) 1998 Van Belle (10.1016/j.cie.2017.01.004_b0100) 2012; 40 Pongchairerks (10.1016/j.cie.2017.01.004_b0080) 2009; 4 |
| References_xml | – volume: 32 start-page: 135 year: 2010 end-page: 161 ident: b0025 article-title: Scheduling inbound and outbound trucks at cross docking terminals publication-title: OR Spectrum – volume: 184 start-page: 377 year: 2008 end-page: 396 ident: b0110 article-title: Scheduling of inbound and outbound trucks in cross docking systems with temporary storage publication-title: European Journal of Operational Research – volume: 4 start-page: 390 year: 2009 end-page: 411 ident: b0080 article-title: A two-level particle swarm optimisation algorithm in job-shop scheduling problems publication-title: International Journal of Operational Research – volume: 6 start-page: 83 year: 2011 end-page: 92 ident: b0085 article-title: A Two-Stage PSO Algorithm for Job Shop Scheduling Problem publication-title: International Journal of Management Science and Engineering Management – volume: 72 start-page: 43 year: 2014 end-page: 49 ident: b0060 article-title: A sequential priority-based heuristic for scheduling material handling in a satellite cross-dock publication-title: Computers & Industrial Engineering – volume: 40 start-page: 5532 year: 2013 end-page: 5541 ident: b0050 article-title: Optimizing truck sequencing and truck dock assignment in a cross docking system publication-title: Expert Systems with Applications – volume: 56 start-page: 1309 year: 2009 end-page: 1318 ident: b0115 article-title: An effective hybrid particle swarm optimization algorithm to multi-objective flexible job-shop scheduling problem publication-title: Computers & Industrial Engineering – reference: (pp. 799–803). Haikou. – volume: 39 start-page: 2564 year: 2012 end-page: 2577 ident: b0090 article-title: A robust two-phase heuristic algorithm for the truck scheduling problem in a resource-constrained crossdock publication-title: Computers & Operations Research – volume: 90 start-page: 221 year: 2015 end-page: 240 ident: b0070 article-title: A novel dynamic genetic algorithm-based method for vehicle scheduling in cross docking systems with frequent unloading operation publication-title: Computers & Industrial Engineering – volume: 38 start-page: 413 year: 2010 end-page: 422 ident: b0020 article-title: Cross dock scheduling: Classification, literature review and research agenda publication-title: OMEGA – volume: 38 start-page: 1964 year: 2011 end-page: 1979 ident: b0010 article-title: Metaheuristics implementation for scheduling of trucks in a cross-docking system with temporary storage publication-title: Expert Systems with Applications – volume: 193 start-page: 59 year: 2009 end-page: 72 ident: b0030 article-title: Minimizing the makespan in a two-machine cross-docking flow shop problem publication-title: European Journal of Operational Research – reference: Liu, Z. (2007). Investigation of particle swarm optimization for job shop scheduling problem. In – volume: 6 start-page: 176 year: 2009 end-page: 194 ident: b0075 article-title: Particle swarm optimization algorithm with multiple social learning structures publication-title: International Journal of Operational Research – volume: 49 start-page: 741 year: 2010 end-page: 756 ident: b0005 article-title: A multi-criteria cross docking scheduling with just-in-time approach publication-title: The International Journal of Advanced Manufacturing Technology – volume: 91 start-page: 197 year: 2016 end-page: 204 ident: b0045 article-title: An improved mathematical model and a hybrid metaheuristic for truck scheduling in cross-dock problems publication-title: Computers & Industrial Engineering – volume: 36 start-page: 2066 year: 2009 end-page: 2073 ident: b0035 article-title: Minimizing makespan in two-stage hybrid cross docking scheduling problem publication-title: Computers & Operations Research – reference: Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. In – volume: 92 start-page: 50 year: 2016 end-page: 56 ident: b0095 article-title: Cross dock scheduling with fixed outbound trucks departure time under substitution condition publication-title: Computers & Industrial Engineering – volume: 40 start-page: 827 year: 2012 end-page: 846 ident: b0100 article-title: Cross-docking: State of the art publication-title: Omega – reference: (pp. 1942–1948). Perth, WA. – volume: 66 start-page: 818 year: 2013 end-page: 826 ident: b0105 article-title: A tabu search approach to the truck scheduling problem with multiple docks and time windows publication-title: Computers & Industrial Engineering – volume: 74 start-page: 129 year: 2014 end-page: 138 ident: b0065 article-title: Multiple cross-docks scheduling using two meta-heuristic algorithms publication-title: Computers & Industrial Engineering – start-page: 69 year: 1998 end-page: 73 ident: b9005 article-title: A modified particle swarm optimizer publication-title: 1998 IEEE international conference on evolutionary computation proceedings – volume: 92 start-page: 50 year: 2016 ident: 10.1016/j.cie.2017.01.004_b0095 article-title: Cross dock scheduling with fixed outbound trucks departure time under substitution condition publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2015.12.005 – volume: 40 start-page: 827 issue: 6 year: 2012 ident: 10.1016/j.cie.2017.01.004_b0100 article-title: Cross-docking: State of the art publication-title: Omega doi: 10.1016/j.omega.2012.01.005 – volume: 193 start-page: 59 issue: 1 year: 2009 ident: 10.1016/j.cie.2017.01.004_b0030 article-title: Minimizing the makespan in a two-machine cross-docking flow shop problem publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2007.10.051 – volume: 6 start-page: 83 issue: 2 year: 2011 ident: 10.1016/j.cie.2017.01.004_b0085 article-title: A Two-Stage PSO Algorithm for Job Shop Scheduling Problem publication-title: International Journal of Management Science and Engineering Management doi: 10.1080/17509653.2011.10671149 – volume: 56 start-page: 1309 issue: 4 year: 2009 ident: 10.1016/j.cie.2017.01.004_b0115 article-title: An effective hybrid particle swarm optimization algorithm to multi-objective flexible job-shop scheduling problem publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2008.07.021 – volume: 39 start-page: 2564 issue: 11 year: 2012 ident: 10.1016/j.cie.2017.01.004_b0090 article-title: A robust two-phase heuristic algorithm for the truck scheduling problem in a resource-constrained crossdock publication-title: Computers & Operations Research doi: 10.1016/j.cor.2012.01.002 – volume: 38 start-page: 413 issue: 6 year: 2010 ident: 10.1016/j.cie.2017.01.004_b0020 article-title: Cross dock scheduling: Classification, literature review and research agenda publication-title: OMEGA doi: 10.1016/j.omega.2009.10.008 – volume: 49 start-page: 741 issue: 5–8 year: 2010 ident: 10.1016/j.cie.2017.01.004_b0005 article-title: A multi-criteria cross docking scheduling with just-in-time approach publication-title: The International Journal of Advanced Manufacturing Technology doi: 10.1007/s00170-009-2429-5 – volume: 40 start-page: 5532 issue: 14 year: 2013 ident: 10.1016/j.cie.2017.01.004_b0050 article-title: Optimizing truck sequencing and truck dock assignment in a cross docking system publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2013.04.019 – volume: 74 start-page: 129 year: 2014 ident: 10.1016/j.cie.2017.01.004_b0065 article-title: Multiple cross-docks scheduling using two meta-heuristic algorithms publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2014.05.009 – volume: 38 start-page: 1964 issue: 3 year: 2011 ident: 10.1016/j.cie.2017.01.004_b0010 article-title: Metaheuristics implementation for scheduling of trucks in a cross-docking system with temporary storage publication-title: Expert Systems with Applications doi: 10.1016/j.eswa.2010.07.130 – volume: 66 start-page: 818 issue: 4 year: 2013 ident: 10.1016/j.cie.2017.01.004_b0105 article-title: A tabu search approach to the truck scheduling problem with multiple docks and time windows publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2013.09.024 – volume: 36 start-page: 2066 issue: 6 year: 2009 ident: 10.1016/j.cie.2017.01.004_b0035 article-title: Minimizing makespan in two-stage hybrid cross docking scheduling problem publication-title: Computers & Operations Research doi: 10.1016/j.cor.2008.07.003 – ident: 10.1016/j.cie.2017.01.004_b0055 doi: 10.1109/ICNC.2007.453 – volume: 6 start-page: 176 issue: 2 year: 2009 ident: 10.1016/j.cie.2017.01.004_b0075 article-title: Particle swarm optimization algorithm with multiple social learning structures publication-title: International Journal of Operational Research doi: 10.1504/IJOR.2009.026534 – start-page: 69 year: 1998 ident: 10.1016/j.cie.2017.01.004_b9005 article-title: A modified particle swarm optimizer – volume: 184 start-page: 377 issue: 1 year: 2008 ident: 10.1016/j.cie.2017.01.004_b0110 article-title: Scheduling of inbound and outbound trucks in cross docking systems with temporary storage publication-title: European Journal of Operational Research doi: 10.1016/j.ejor.2006.10.047 – volume: 91 start-page: 197 year: 2016 ident: 10.1016/j.cie.2017.01.004_b0045 article-title: An improved mathematical model and a hybrid metaheuristic for truck scheduling in cross-dock problems publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2015.11.006 – volume: 32 start-page: 135 issue: 1 year: 2010 ident: 10.1016/j.cie.2017.01.004_b0025 article-title: Scheduling inbound and outbound trucks at cross docking terminals publication-title: OR Spectrum doi: 10.1007/s00291-008-0139-2 – volume: 72 start-page: 43 year: 2014 ident: 10.1016/j.cie.2017.01.004_b0060 article-title: A sequential priority-based heuristic for scheduling material handling in a satellite cross-dock publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2014.03.002 – ident: 10.1016/j.cie.2017.01.004_b0040 doi: 10.1109/ICNN.1995.488968 – volume: 90 start-page: 221 year: 2015 ident: 10.1016/j.cie.2017.01.004_b0070 article-title: A novel dynamic genetic algorithm-based method for vehicle scheduling in cross docking systems with frequent unloading operation publication-title: Computers & Industrial Engineering doi: 10.1016/j.cie.2015.09.008 – volume: 4 start-page: 390 issue: 4 year: 2009 ident: 10.1016/j.cie.2017.01.004_b0080 article-title: A two-level particle swarm optimisation algorithm in job-shop scheduling problems publication-title: International Journal of Operational Research doi: 10.1504/IJOR.2009.023535 |
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