Adjusting the order crossover operator for capacitated vehicle routing problems
The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics ava...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Hvattum, Lars Magnus [verfasserIn] |
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E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Influence of CeO - Aboutaleb, Wael A. ELSEVIER, 2021, an international journal, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:148 ; year:2022 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.cor.2022.105986 |
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| 520 | |a The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. | ||
| 520 | |a The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. | ||
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10.1016/j.cor.2022.105986 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001907.pica (DE-627)ELV058990445 (ELSEVIER)S0305-0548(22)00224-6 DE-627 ger DE-627 rakwb eng 540 530 VZ ASIEN DE-1a fid 6,25 ssgn 35.90 bkl 33.61 bkl 51.00 bkl Hvattum, Lars Magnus verfasserin aut Adjusting the order crossover operator for capacitated vehicle routing problems 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. Genetic algorithm Elsevier Genetic operator Elsevier Vehicle routing problem Elsevier Open source Elsevier Enthalten in Elsevier Aboutaleb, Wael A. ELSEVIER Influence of CeO 2021 an international journal Amsterdam [u.a.] (DE-627)ELV00698584X volume:148 year:2022 pages:0 https://doi.org/10.1016/j.cor.2022.105986 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-ASIEN SSG-OLC-PHA 35.90 Festkörperchemie VZ 33.61 Festkörperphysik VZ 51.00 Werkstoffkunde: Allgemeines VZ AR 148 2022 0 |
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10.1016/j.cor.2022.105986 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001907.pica (DE-627)ELV058990445 (ELSEVIER)S0305-0548(22)00224-6 DE-627 ger DE-627 rakwb eng 540 530 VZ ASIEN DE-1a fid 6,25 ssgn 35.90 bkl 33.61 bkl 51.00 bkl Hvattum, Lars Magnus verfasserin aut Adjusting the order crossover operator for capacitated vehicle routing problems 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. Genetic algorithm Elsevier Genetic operator Elsevier Vehicle routing problem Elsevier Open source Elsevier Enthalten in Elsevier Aboutaleb, Wael A. ELSEVIER Influence of CeO 2021 an international journal Amsterdam [u.a.] (DE-627)ELV00698584X volume:148 year:2022 pages:0 https://doi.org/10.1016/j.cor.2022.105986 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-ASIEN SSG-OLC-PHA 35.90 Festkörperchemie VZ 33.61 Festkörperphysik VZ 51.00 Werkstoffkunde: Allgemeines VZ AR 148 2022 0 |
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10.1016/j.cor.2022.105986 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001907.pica (DE-627)ELV058990445 (ELSEVIER)S0305-0548(22)00224-6 DE-627 ger DE-627 rakwb eng 540 530 VZ ASIEN DE-1a fid 6,25 ssgn 35.90 bkl 33.61 bkl 51.00 bkl Hvattum, Lars Magnus verfasserin aut Adjusting the order crossover operator for capacitated vehicle routing problems 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. Genetic algorithm Elsevier Genetic operator Elsevier Vehicle routing problem Elsevier Open source Elsevier Enthalten in Elsevier Aboutaleb, Wael A. ELSEVIER Influence of CeO 2021 an international journal Amsterdam [u.a.] (DE-627)ELV00698584X volume:148 year:2022 pages:0 https://doi.org/10.1016/j.cor.2022.105986 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-ASIEN SSG-OLC-PHA 35.90 Festkörperchemie VZ 33.61 Festkörperphysik VZ 51.00 Werkstoffkunde: Allgemeines VZ AR 148 2022 0 |
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Adjusting the order crossover operator for capacitated vehicle routing problems |
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The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. |
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The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. |
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The capacitated vehicle routing problem is a much studied combinatorial optimization problem, reflecting its practical importance within areas such as logistics. The problem is computationally intractable, and heuristics are commonly applied for solving large instances. Among the best heuristics available is a hybrid genetic search that consists of mechanisms from evolutionary algorithms and a range of local search operators. This heuristic applies an order crossover operator that takes as input two existing solutions and produces as output a new solution for the search to explore. An open-source implementation of the heuristic is available, in which the order crossover operator represents 1.4% of the code. This work discusses potential short-comings of the traditional order crossover operator and proposes an adjusted operator. The new operator is evaluated on standard benchmark test instances, and is shown to reduce the gaps to best-known solutions by 4.2%. |
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Adjusting the order crossover operator for capacitated vehicle routing problems |
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