On investigation of interdependence between sub-problems of the Travelling Thief Problem
Abstract In this paper, the interdependence between sub-problems in a complex overall problem is investigated using a benchmark problem called Travelling Thief Problem (TTP), which is a combination of Travelling Salesman Problem (TSP) and Knapsack Problem (KP). First, the analysis on the mathematica...
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Gespeichert in:
| Autor*in: |
Mei, Yi [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag Berlin Heidelberg 2014 |
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| Übergeordnetes Werk: |
Enthalten in: Soft computing - Springer Berlin Heidelberg, 1997, 20(2014), 1 vom: 17. Okt., Seite 157-172 |
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| Übergeordnetes Werk: |
volume:20 ; year:2014 ; number:1 ; day:17 ; month:10 ; pages:157-172 |
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| DOI / URN: |
10.1007/s00500-014-1487-2 |
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OLC2034879449 |
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| 520 | |a Abstract In this paper, the interdependence between sub-problems in a complex overall problem is investigated using a benchmark problem called Travelling Thief Problem (TTP), which is a combination of Travelling Salesman Problem (TSP) and Knapsack Problem (KP). First, the analysis on the mathematical formulation shows that it is impossible to decompose the problem into independent sub-problems due to the non-linear relationship in the objective function. Therefore, the algorithm for TTP is not straightforward although each sub-problem alone has been investigated intensively. Then, two meta-heuristics are proposed for TTP. One is the Cooperative Co-evolution (CC) that solves the sub-problems separately and transfers the information between them in each generation. The other is the Memetic Algorithm (MA) that solves TTP as a whole. The comparative results showed that MA consistently obtained much better results than both the standard and dynamic versions of CC within comparable computational budget. This indicates the importance of considering the interdependence between sub-problems in an overall problem like TTP. | ||
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| 650 | 4 | |a Evolutionary computation | |
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| 700 | 1 | |a Li, Xiaodong |4 aut | |
| 700 | 1 | |a Yao, Xin |4 aut | |
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10.1007/s00500-014-1487-2 doi (DE-627)OLC2034879449 (DE-He213)s00500-014-1487-2-p DE-627 ger DE-627 rakwb eng 004 VZ 004 VZ 11 ssgn Mei, Yi verfasserin aut On investigation of interdependence between sub-problems of the Travelling Thief Problem 2014 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2014 Abstract In this paper, the interdependence between sub-problems in a complex overall problem is investigated using a benchmark problem called Travelling Thief Problem (TTP), which is a combination of Travelling Salesman Problem (TSP) and Knapsack Problem (KP). First, the analysis on the mathematical formulation shows that it is impossible to decompose the problem into independent sub-problems due to the non-linear relationship in the objective function. Therefore, the algorithm for TTP is not straightforward although each sub-problem alone has been investigated intensively. Then, two meta-heuristics are proposed for TTP. One is the Cooperative Co-evolution (CC) that solves the sub-problems separately and transfers the information between them in each generation. The other is the Memetic Algorithm (MA) that solves TTP as a whole. The comparative results showed that MA consistently obtained much better results than both the standard and dynamic versions of CC within comparable computational budget. This indicates the importance of considering the interdependence between sub-problems in an overall problem like TTP. Combinatorial optimization Evolutionary computation Cooperative Co-evolution Travelling Thief Problem Interdependence Li, Xiaodong aut Yao, Xin aut Enthalten in Soft computing Springer Berlin Heidelberg, 1997 20(2014), 1 vom: 17. Okt., Seite 157-172 (DE-627)231970536 (DE-600)1387526-7 (DE-576)060238259 1432-7643 nnns volume:20 year:2014 number:1 day:17 month:10 pages:157-172 https://doi.org/10.1007/s00500-014-1487-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 20 2014 1 17 10 157-172 |
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10.1007/s00500-014-1487-2 doi (DE-627)OLC2034879449 (DE-He213)s00500-014-1487-2-p DE-627 ger DE-627 rakwb eng 004 VZ 004 VZ 11 ssgn Mei, Yi verfasserin aut On investigation of interdependence between sub-problems of the Travelling Thief Problem 2014 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2014 Abstract In this paper, the interdependence between sub-problems in a complex overall problem is investigated using a benchmark problem called Travelling Thief Problem (TTP), which is a combination of Travelling Salesman Problem (TSP) and Knapsack Problem (KP). First, the analysis on the mathematical formulation shows that it is impossible to decompose the problem into independent sub-problems due to the non-linear relationship in the objective function. Therefore, the algorithm for TTP is not straightforward although each sub-problem alone has been investigated intensively. Then, two meta-heuristics are proposed for TTP. One is the Cooperative Co-evolution (CC) that solves the sub-problems separately and transfers the information between them in each generation. The other is the Memetic Algorithm (MA) that solves TTP as a whole. The comparative results showed that MA consistently obtained much better results than both the standard and dynamic versions of CC within comparable computational budget. This indicates the importance of considering the interdependence between sub-problems in an overall problem like TTP. Combinatorial optimization Evolutionary computation Cooperative Co-evolution Travelling Thief Problem Interdependence Li, Xiaodong aut Yao, Xin aut Enthalten in Soft computing Springer Berlin Heidelberg, 1997 20(2014), 1 vom: 17. Okt., Seite 157-172 (DE-627)231970536 (DE-600)1387526-7 (DE-576)060238259 1432-7643 nnns volume:20 year:2014 number:1 day:17 month:10 pages:157-172 https://doi.org/10.1007/s00500-014-1487-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 20 2014 1 17 10 157-172 |
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10.1007/s00500-014-1487-2 doi (DE-627)OLC2034879449 (DE-He213)s00500-014-1487-2-p DE-627 ger DE-627 rakwb eng 004 VZ 004 VZ 11 ssgn Mei, Yi verfasserin aut On investigation of interdependence between sub-problems of the Travelling Thief Problem 2014 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2014 Abstract In this paper, the interdependence between sub-problems in a complex overall problem is investigated using a benchmark problem called Travelling Thief Problem (TTP), which is a combination of Travelling Salesman Problem (TSP) and Knapsack Problem (KP). First, the analysis on the mathematical formulation shows that it is impossible to decompose the problem into independent sub-problems due to the non-linear relationship in the objective function. Therefore, the algorithm for TTP is not straightforward although each sub-problem alone has been investigated intensively. Then, two meta-heuristics are proposed for TTP. One is the Cooperative Co-evolution (CC) that solves the sub-problems separately and transfers the information between them in each generation. The other is the Memetic Algorithm (MA) that solves TTP as a whole. The comparative results showed that MA consistently obtained much better results than both the standard and dynamic versions of CC within comparable computational budget. This indicates the importance of considering the interdependence between sub-problems in an overall problem like TTP. Combinatorial optimization Evolutionary computation Cooperative Co-evolution Travelling Thief Problem Interdependence Li, Xiaodong aut Yao, Xin aut Enthalten in Soft computing Springer Berlin Heidelberg, 1997 20(2014), 1 vom: 17. Okt., Seite 157-172 (DE-627)231970536 (DE-600)1387526-7 (DE-576)060238259 1432-7643 nnns volume:20 year:2014 number:1 day:17 month:10 pages:157-172 https://doi.org/10.1007/s00500-014-1487-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 20 2014 1 17 10 157-172 |
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10.1007/s00500-014-1487-2 doi (DE-627)OLC2034879449 (DE-He213)s00500-014-1487-2-p DE-627 ger DE-627 rakwb eng 004 VZ 004 VZ 11 ssgn Mei, Yi verfasserin aut On investigation of interdependence between sub-problems of the Travelling Thief Problem 2014 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag Berlin Heidelberg 2014 Abstract In this paper, the interdependence between sub-problems in a complex overall problem is investigated using a benchmark problem called Travelling Thief Problem (TTP), which is a combination of Travelling Salesman Problem (TSP) and Knapsack Problem (KP). First, the analysis on the mathematical formulation shows that it is impossible to decompose the problem into independent sub-problems due to the non-linear relationship in the objective function. Therefore, the algorithm for TTP is not straightforward although each sub-problem alone has been investigated intensively. Then, two meta-heuristics are proposed for TTP. One is the Cooperative Co-evolution (CC) that solves the sub-problems separately and transfers the information between them in each generation. The other is the Memetic Algorithm (MA) that solves TTP as a whole. The comparative results showed that MA consistently obtained much better results than both the standard and dynamic versions of CC within comparable computational budget. This indicates the importance of considering the interdependence between sub-problems in an overall problem like TTP. Combinatorial optimization Evolutionary computation Cooperative Co-evolution Travelling Thief Problem Interdependence Li, Xiaodong aut Yao, Xin aut Enthalten in Soft computing Springer Berlin Heidelberg, 1997 20(2014), 1 vom: 17. Okt., Seite 157-172 (DE-627)231970536 (DE-600)1387526-7 (DE-576)060238259 1432-7643 nnns volume:20 year:2014 number:1 day:17 month:10 pages:157-172 https://doi.org/10.1007/s00500-014-1487-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 20 2014 1 17 10 157-172 |
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Abstract In this paper, the interdependence between sub-problems in a complex overall problem is investigated using a benchmark problem called Travelling Thief Problem (TTP), which is a combination of Travelling Salesman Problem (TSP) and Knapsack Problem (KP). First, the analysis on the mathematical formulation shows that it is impossible to decompose the problem into independent sub-problems due to the non-linear relationship in the objective function. Therefore, the algorithm for TTP is not straightforward although each sub-problem alone has been investigated intensively. Then, two meta-heuristics are proposed for TTP. One is the Cooperative Co-evolution (CC) that solves the sub-problems separately and transfers the information between them in each generation. The other is the Memetic Algorithm (MA) that solves TTP as a whole. The comparative results showed that MA consistently obtained much better results than both the standard and dynamic versions of CC within comparable computational budget. This indicates the importance of considering the interdependence between sub-problems in an overall problem like TTP. © Springer-Verlag Berlin Heidelberg 2014 |
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Abstract In this paper, the interdependence between sub-problems in a complex overall problem is investigated using a benchmark problem called Travelling Thief Problem (TTP), which is a combination of Travelling Salesman Problem (TSP) and Knapsack Problem (KP). First, the analysis on the mathematical formulation shows that it is impossible to decompose the problem into independent sub-problems due to the non-linear relationship in the objective function. Therefore, the algorithm for TTP is not straightforward although each sub-problem alone has been investigated intensively. Then, two meta-heuristics are proposed for TTP. One is the Cooperative Co-evolution (CC) that solves the sub-problems separately and transfers the information between them in each generation. The other is the Memetic Algorithm (MA) that solves TTP as a whole. The comparative results showed that MA consistently obtained much better results than both the standard and dynamic versions of CC within comparable computational budget. This indicates the importance of considering the interdependence between sub-problems in an overall problem like TTP. © Springer-Verlag Berlin Heidelberg 2014 |
| abstract_unstemmed |
Abstract In this paper, the interdependence between sub-problems in a complex overall problem is investigated using a benchmark problem called Travelling Thief Problem (TTP), which is a combination of Travelling Salesman Problem (TSP) and Knapsack Problem (KP). First, the analysis on the mathematical formulation shows that it is impossible to decompose the problem into independent sub-problems due to the non-linear relationship in the objective function. Therefore, the algorithm for TTP is not straightforward although each sub-problem alone has been investigated intensively. Then, two meta-heuristics are proposed for TTP. One is the Cooperative Co-evolution (CC) that solves the sub-problems separately and transfers the information between them in each generation. The other is the Memetic Algorithm (MA) that solves TTP as a whole. The comparative results showed that MA consistently obtained much better results than both the standard and dynamic versions of CC within comparable computational budget. This indicates the importance of considering the interdependence between sub-problems in an overall problem like TTP. © Springer-Verlag Berlin Heidelberg 2014 |
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On investigation of interdependence between sub-problems of the Travelling Thief Problem |
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Li, Xiaodong Yao, Xin |
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