Reducing Multivalued Discrete Variables in Solving Separable Task Assignment Problems
Abstract In this paper, we introduce the separable task assignment problem (STAP) in which n separable tasks are assigned to m agents subject to agents’ capacity constraints. The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is se...
Ausführliche Beschreibung
Autor*in: |
Gai, Ling [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2015 |
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Schlagwörter: |
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Anmerkung: |
© Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press and Springer-Verlag Berlin Heidelberg 2015 |
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Übergeordnetes Werk: |
Enthalten in: Journal of the operations research society of China - Berlin : Springer, 2013, 4(2015), 1 vom: 08. Juli, Seite 97-110 |
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Übergeordnetes Werk: |
volume:4 ; year:2015 ; number:1 ; day:08 ; month:07 ; pages:97-110 |
Links: |
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DOI / URN: |
10.1007/s40305-015-0087-x |
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Katalog-ID: |
SPR036577472 |
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520 | |a Abstract In this paper, we introduce the separable task assignment problem (STAP) in which n separable tasks are assigned to m agents subject to agents’ capacity constraints. The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is separable if it can be divided into two pieces, and both of them can be assigned individually or together to any agents. A separable task is considered as being assigned if and only if its two pieces are both assigned. Since several discrete (ternary) variables may be involved in STAP modeling, computing the problem in a reasonable time period is not an easy work. We replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al. (INFORMS J Comput 25(4): 643–653, 2012) and Vielma et al. (Oper Res 58(2): 303–315, 2010). Our numerical experiments demonstrate that the newly generated model performs well in solving difficult separable task-assignment problems for pretty large scale of instance sizes. | ||
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650 | 4 | |a Mixed integer programming problem |7 (dpeaa)DE-He213 | |
700 | 1 | |a Jin, Qing-Wei |4 aut | |
700 | 1 | |a Tian, Yuan |4 aut | |
700 | 1 | |a Huang, Yao-Huei |4 aut | |
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10.1007/s40305-015-0087-x doi (DE-627)SPR036577472 (SPR)s40305-015-0087-x-e DE-627 ger DE-627 rakwb eng Gai, Ling verfasserin aut Reducing Multivalued Discrete Variables in Solving Separable Task Assignment Problems 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press and Springer-Verlag Berlin Heidelberg 2015 Abstract In this paper, we introduce the separable task assignment problem (STAP) in which n separable tasks are assigned to m agents subject to agents’ capacity constraints. The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is separable if it can be divided into two pieces, and both of them can be assigned individually or together to any agents. A separable task is considered as being assigned if and only if its two pieces are both assigned. Since several discrete (ternary) variables may be involved in STAP modeling, computing the problem in a reasonable time period is not an easy work. We replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al. (INFORMS J Comput 25(4): 643–653, 2012) and Vielma et al. (Oper Res 58(2): 303–315, 2010). Our numerical experiments demonstrate that the newly generated model performs well in solving difficult separable task-assignment problems for pretty large scale of instance sizes. Task-assignment problem (dpeaa)DE-He213 Ternary variables (dpeaa)DE-He213 Binary variables (dpeaa)DE-He213 Mixed integer programming problem (dpeaa)DE-He213 Jin, Qing-Wei aut Tian, Yuan aut Huang, Yao-Huei aut Enthalten in Journal of the operations research society of China Berlin : Springer, 2013 4(2015), 1 vom: 08. Juli, Seite 97-110 (DE-627)739215051 (DE-600)2708006-7 2194-6698 nnns volume:4 year:2015 number:1 day:08 month:07 pages:97-110 https://dx.doi.org/10.1007/s40305-015-0087-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 4 2015 1 08 07 97-110 |
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10.1007/s40305-015-0087-x doi (DE-627)SPR036577472 (SPR)s40305-015-0087-x-e DE-627 ger DE-627 rakwb eng Gai, Ling verfasserin aut Reducing Multivalued Discrete Variables in Solving Separable Task Assignment Problems 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press and Springer-Verlag Berlin Heidelberg 2015 Abstract In this paper, we introduce the separable task assignment problem (STAP) in which n separable tasks are assigned to m agents subject to agents’ capacity constraints. The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is separable if it can be divided into two pieces, and both of them can be assigned individually or together to any agents. A separable task is considered as being assigned if and only if its two pieces are both assigned. Since several discrete (ternary) variables may be involved in STAP modeling, computing the problem in a reasonable time period is not an easy work. We replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al. (INFORMS J Comput 25(4): 643–653, 2012) and Vielma et al. (Oper Res 58(2): 303–315, 2010). Our numerical experiments demonstrate that the newly generated model performs well in solving difficult separable task-assignment problems for pretty large scale of instance sizes. Task-assignment problem (dpeaa)DE-He213 Ternary variables (dpeaa)DE-He213 Binary variables (dpeaa)DE-He213 Mixed integer programming problem (dpeaa)DE-He213 Jin, Qing-Wei aut Tian, Yuan aut Huang, Yao-Huei aut Enthalten in Journal of the operations research society of China Berlin : Springer, 2013 4(2015), 1 vom: 08. Juli, Seite 97-110 (DE-627)739215051 (DE-600)2708006-7 2194-6698 nnns volume:4 year:2015 number:1 day:08 month:07 pages:97-110 https://dx.doi.org/10.1007/s40305-015-0087-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 4 2015 1 08 07 97-110 |
allfields_unstemmed |
10.1007/s40305-015-0087-x doi (DE-627)SPR036577472 (SPR)s40305-015-0087-x-e DE-627 ger DE-627 rakwb eng Gai, Ling verfasserin aut Reducing Multivalued Discrete Variables in Solving Separable Task Assignment Problems 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press and Springer-Verlag Berlin Heidelberg 2015 Abstract In this paper, we introduce the separable task assignment problem (STAP) in which n separable tasks are assigned to m agents subject to agents’ capacity constraints. The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is separable if it can be divided into two pieces, and both of them can be assigned individually or together to any agents. A separable task is considered as being assigned if and only if its two pieces are both assigned. Since several discrete (ternary) variables may be involved in STAP modeling, computing the problem in a reasonable time period is not an easy work. We replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al. (INFORMS J Comput 25(4): 643–653, 2012) and Vielma et al. (Oper Res 58(2): 303–315, 2010). Our numerical experiments demonstrate that the newly generated model performs well in solving difficult separable task-assignment problems for pretty large scale of instance sizes. Task-assignment problem (dpeaa)DE-He213 Ternary variables (dpeaa)DE-He213 Binary variables (dpeaa)DE-He213 Mixed integer programming problem (dpeaa)DE-He213 Jin, Qing-Wei aut Tian, Yuan aut Huang, Yao-Huei aut Enthalten in Journal of the operations research society of China Berlin : Springer, 2013 4(2015), 1 vom: 08. Juli, Seite 97-110 (DE-627)739215051 (DE-600)2708006-7 2194-6698 nnns volume:4 year:2015 number:1 day:08 month:07 pages:97-110 https://dx.doi.org/10.1007/s40305-015-0087-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 4 2015 1 08 07 97-110 |
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10.1007/s40305-015-0087-x doi (DE-627)SPR036577472 (SPR)s40305-015-0087-x-e DE-627 ger DE-627 rakwb eng Gai, Ling verfasserin aut Reducing Multivalued Discrete Variables in Solving Separable Task Assignment Problems 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press and Springer-Verlag Berlin Heidelberg 2015 Abstract In this paper, we introduce the separable task assignment problem (STAP) in which n separable tasks are assigned to m agents subject to agents’ capacity constraints. The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is separable if it can be divided into two pieces, and both of them can be assigned individually or together to any agents. A separable task is considered as being assigned if and only if its two pieces are both assigned. Since several discrete (ternary) variables may be involved in STAP modeling, computing the problem in a reasonable time period is not an easy work. We replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al. (INFORMS J Comput 25(4): 643–653, 2012) and Vielma et al. (Oper Res 58(2): 303–315, 2010). Our numerical experiments demonstrate that the newly generated model performs well in solving difficult separable task-assignment problems for pretty large scale of instance sizes. Task-assignment problem (dpeaa)DE-He213 Ternary variables (dpeaa)DE-He213 Binary variables (dpeaa)DE-He213 Mixed integer programming problem (dpeaa)DE-He213 Jin, Qing-Wei aut Tian, Yuan aut Huang, Yao-Huei aut Enthalten in Journal of the operations research society of China Berlin : Springer, 2013 4(2015), 1 vom: 08. Juli, Seite 97-110 (DE-627)739215051 (DE-600)2708006-7 2194-6698 nnns volume:4 year:2015 number:1 day:08 month:07 pages:97-110 https://dx.doi.org/10.1007/s40305-015-0087-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 4 2015 1 08 07 97-110 |
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10.1007/s40305-015-0087-x doi (DE-627)SPR036577472 (SPR)s40305-015-0087-x-e DE-627 ger DE-627 rakwb eng Gai, Ling verfasserin aut Reducing Multivalued Discrete Variables in Solving Separable Task Assignment Problems 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press and Springer-Verlag Berlin Heidelberg 2015 Abstract In this paper, we introduce the separable task assignment problem (STAP) in which n separable tasks are assigned to m agents subject to agents’ capacity constraints. The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is separable if it can be divided into two pieces, and both of them can be assigned individually or together to any agents. A separable task is considered as being assigned if and only if its two pieces are both assigned. Since several discrete (ternary) variables may be involved in STAP modeling, computing the problem in a reasonable time period is not an easy work. We replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al. (INFORMS J Comput 25(4): 643–653, 2012) and Vielma et al. (Oper Res 58(2): 303–315, 2010). Our numerical experiments demonstrate that the newly generated model performs well in solving difficult separable task-assignment problems for pretty large scale of instance sizes. Task-assignment problem (dpeaa)DE-He213 Ternary variables (dpeaa)DE-He213 Binary variables (dpeaa)DE-He213 Mixed integer programming problem (dpeaa)DE-He213 Jin, Qing-Wei aut Tian, Yuan aut Huang, Yao-Huei aut Enthalten in Journal of the operations research society of China Berlin : Springer, 2013 4(2015), 1 vom: 08. Juli, Seite 97-110 (DE-627)739215051 (DE-600)2708006-7 2194-6698 nnns volume:4 year:2015 number:1 day:08 month:07 pages:97-110 https://dx.doi.org/10.1007/s40305-015-0087-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2018 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4277 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 4 2015 1 08 07 97-110 |
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Gai, Ling @@aut@@ Jin, Qing-Wei @@aut@@ Tian, Yuan @@aut@@ Huang, Yao-Huei @@aut@@ |
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Gai, Ling misc Task-assignment problem misc Ternary variables misc Binary variables misc Mixed integer programming problem Reducing Multivalued Discrete Variables in Solving Separable Task Assignment Problems |
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Reducing Multivalued Discrete Variables in Solving Separable Task Assignment Problems Task-assignment problem (dpeaa)DE-He213 Ternary variables (dpeaa)DE-He213 Binary variables (dpeaa)DE-He213 Mixed integer programming problem (dpeaa)DE-He213 |
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reducing multivalued discrete variables in solving separable task assignment problems |
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Reducing Multivalued Discrete Variables in Solving Separable Task Assignment Problems |
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Abstract In this paper, we introduce the separable task assignment problem (STAP) in which n separable tasks are assigned to m agents subject to agents’ capacity constraints. The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is separable if it can be divided into two pieces, and both of them can be assigned individually or together to any agents. A separable task is considered as being assigned if and only if its two pieces are both assigned. Since several discrete (ternary) variables may be involved in STAP modeling, computing the problem in a reasonable time period is not an easy work. We replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al. (INFORMS J Comput 25(4): 643–653, 2012) and Vielma et al. (Oper Res 58(2): 303–315, 2010). Our numerical experiments demonstrate that the newly generated model performs well in solving difficult separable task-assignment problems for pretty large scale of instance sizes. © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press and Springer-Verlag Berlin Heidelberg 2015 |
abstractGer |
Abstract In this paper, we introduce the separable task assignment problem (STAP) in which n separable tasks are assigned to m agents subject to agents’ capacity constraints. The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is separable if it can be divided into two pieces, and both of them can be assigned individually or together to any agents. A separable task is considered as being assigned if and only if its two pieces are both assigned. Since several discrete (ternary) variables may be involved in STAP modeling, computing the problem in a reasonable time period is not an easy work. We replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al. (INFORMS J Comput 25(4): 643–653, 2012) and Vielma et al. (Oper Res 58(2): 303–315, 2010). Our numerical experiments demonstrate that the newly generated model performs well in solving difficult separable task-assignment problems for pretty large scale of instance sizes. © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press and Springer-Verlag Berlin Heidelberg 2015 |
abstract_unstemmed |
Abstract In this paper, we introduce the separable task assignment problem (STAP) in which n separable tasks are assigned to m agents subject to agents’ capacity constraints. The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is separable if it can be divided into two pieces, and both of them can be assigned individually or together to any agents. A separable task is considered as being assigned if and only if its two pieces are both assigned. Since several discrete (ternary) variables may be involved in STAP modeling, computing the problem in a reasonable time period is not an easy work. We replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al. (INFORMS J Comput 25(4): 643–653, 2012) and Vielma et al. (Oper Res 58(2): 303–315, 2010). Our numerical experiments demonstrate that the newly generated model performs well in solving difficult separable task-assignment problems for pretty large scale of instance sizes. © Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press and Springer-Verlag Berlin Heidelberg 2015 |
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Reducing Multivalued Discrete Variables in Solving Separable Task Assignment Problems |
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The objective is to minimize the costs that occur during the manufacturing and the communication between agents. A task is separable if it can be divided into two pieces, and both of them can be assigned individually or together to any agents. A separable task is considered as being assigned if and only if its two pieces are both assigned. Since several discrete (ternary) variables may be involved in STAP modeling, computing the problem in a reasonable time period is not an easy work. We replace the ternary variables by binary and continuous variables through extending the logarithmic method introduced by Li et al. (INFORMS J Comput 25(4): 643–653, 2012) and Vielma et al. (Oper Res 58(2): 303–315, 2010). 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