A Multi-Objective Robust Optimization Design for Grid Emergency Goods Distribution Under Mixed Uncertainty

Emergency goods distribution plays an important role in the grid emergency relief command system. However, the traditional experience-based distribution plan currently in the power grid cannot meet the increasing demand for the types and quantities of emergency goods, meanwhile, most studies ignore...
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Autor*in:	Yiwen Jiang [verfasserIn] Lee Li [verfasserIn] Zhensheng Liu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	Emergent phenomena resource management Pareto optimization uncertainty heuristic algorithms

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 6(2018), Seite 61117-61129
Übergeordnetes Werk:	volume:6 ; year:2018 ; pages:61117-61129

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2018.2875786

Katalog-ID:	DOAJ071594361

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allfieldsSound	10.1109/ACCESS.2018.2875786 doi (DE-627)DOAJ071594361 (DE-599)DOAJ07bd02f16c7c4fd290e59573d7733aa6 DE-627 ger DE-627 rakwb eng TK1-9971 Yiwen Jiang verfasserin aut A Multi-Objective Robust Optimization Design for Grid Emergency Goods Distribution Under Mixed Uncertainty 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Emergency goods distribution plays an important role in the grid emergency relief command system. However, the traditional experience-based distribution plan currently in the power grid cannot meet the increasing demand for the types and quantities of emergency goods, meanwhile, most studies ignore the uncertainty in distribution parameters and diversification of distribution objectives, which causes a gap between theoretical research and practical application. Therefore, this paper establishes a model to guide the logistics design for transferring relief supplies. The model first assesses the importance of affected areas for determining distribution priority based on the electrical characteristics. To better simulate reality, the uncertainties in demand, supply, and the costs of procurement and transportation are considered. Additionally, the model features three objectives: shortening the travel time, reducing the goods shortage, and saving the total cost of pre- and post-disaster phases. In order to handle the uncertainties, the robust optimization approach is utilized. The numerical example is solved with ε-constraint exact method, and this case illustrates the specific process of goods distribution, the relationship between objectives, and the sensitivity analysis of uncertainties. For the large-size forms, two heuristic algorithms are proposed and the efficiency of the proposed algorithms is assessed. Emergent phenomena resource management Pareto optimization uncertainty heuristic algorithms Electrical engineering. Electronics. Nuclear engineering Lee Li verfasserin aut Zhensheng Liu verfasserin aut In IEEE Access IEEE, 2014 6(2018), Seite 61117-61129 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:6 year:2018 pages:61117-61129 https://doi.org/10.1109/ACCESS.2018.2875786 kostenfrei https://doaj.org/article/07bd02f16c7c4fd290e59573d7733aa6 kostenfrei https://ieeexplore.ieee.org/document/8490822/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2018 61117-61129
language	English
source	In IEEE Access 6(2018), Seite 61117-61129 volume:6 year:2018 pages:61117-61129
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topic_facet	Emergent phenomena resource management Pareto optimization uncertainty heuristic algorithms Electrical engineering. Electronics. Nuclear engineering
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authorswithroles_txt_mv	Yiwen Jiang @@aut@@ Lee Li @@aut@@ Zhensheng Liu @@aut@@
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callnumber-first	T - Technology
author	Yiwen Jiang
spellingShingle	Yiwen Jiang misc TK1-9971 misc Emergent phenomena misc resource management misc Pareto optimization misc uncertainty misc heuristic algorithms misc Electrical engineering. Electronics. Nuclear engineering A Multi-Objective Robust Optimization Design for Grid Emergency Goods Distribution Under Mixed Uncertainty
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topic_title	TK1-9971 A Multi-Objective Robust Optimization Design for Grid Emergency Goods Distribution Under Mixed Uncertainty Emergent phenomena resource management Pareto optimization uncertainty heuristic algorithms
topic	misc TK1-9971 misc Emergent phenomena misc resource management misc Pareto optimization misc uncertainty misc heuristic algorithms misc Electrical engineering. Electronics. Nuclear engineering
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title	A Multi-Objective Robust Optimization Design for Grid Emergency Goods Distribution Under Mixed Uncertainty
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title_sort	multi-objective robust optimization design for grid emergency goods distribution under mixed uncertainty
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title_auth	A Multi-Objective Robust Optimization Design for Grid Emergency Goods Distribution Under Mixed Uncertainty
abstract	Emergency goods distribution plays an important role in the grid emergency relief command system. However, the traditional experience-based distribution plan currently in the power grid cannot meet the increasing demand for the types and quantities of emergency goods, meanwhile, most studies ignore the uncertainty in distribution parameters and diversification of distribution objectives, which causes a gap between theoretical research and practical application. Therefore, this paper establishes a model to guide the logistics design for transferring relief supplies. The model first assesses the importance of affected areas for determining distribution priority based on the electrical characteristics. To better simulate reality, the uncertainties in demand, supply, and the costs of procurement and transportation are considered. Additionally, the model features three objectives: shortening the travel time, reducing the goods shortage, and saving the total cost of pre- and post-disaster phases. In order to handle the uncertainties, the robust optimization approach is utilized. The numerical example is solved with ε-constraint exact method, and this case illustrates the specific process of goods distribution, the relationship between objectives, and the sensitivity analysis of uncertainties. For the large-size forms, two heuristic algorithms are proposed and the efficiency of the proposed algorithms is assessed.
abstractGer	Emergency goods distribution plays an important role in the grid emergency relief command system. However, the traditional experience-based distribution plan currently in the power grid cannot meet the increasing demand for the types and quantities of emergency goods, meanwhile, most studies ignore the uncertainty in distribution parameters and diversification of distribution objectives, which causes a gap between theoretical research and practical application. Therefore, this paper establishes a model to guide the logistics design for transferring relief supplies. The model first assesses the importance of affected areas for determining distribution priority based on the electrical characteristics. To better simulate reality, the uncertainties in demand, supply, and the costs of procurement and transportation are considered. Additionally, the model features three objectives: shortening the travel time, reducing the goods shortage, and saving the total cost of pre- and post-disaster phases. In order to handle the uncertainties, the robust optimization approach is utilized. The numerical example is solved with ε-constraint exact method, and this case illustrates the specific process of goods distribution, the relationship between objectives, and the sensitivity analysis of uncertainties. For the large-size forms, two heuristic algorithms are proposed and the efficiency of the proposed algorithms is assessed.
abstract_unstemmed	Emergency goods distribution plays an important role in the grid emergency relief command system. However, the traditional experience-based distribution plan currently in the power grid cannot meet the increasing demand for the types and quantities of emergency goods, meanwhile, most studies ignore the uncertainty in distribution parameters and diversification of distribution objectives, which causes a gap between theoretical research and practical application. Therefore, this paper establishes a model to guide the logistics design for transferring relief supplies. The model first assesses the importance of affected areas for determining distribution priority based on the electrical characteristics. To better simulate reality, the uncertainties in demand, supply, and the costs of procurement and transportation are considered. Additionally, the model features three objectives: shortening the travel time, reducing the goods shortage, and saving the total cost of pre- and post-disaster phases. In order to handle the uncertainties, the robust optimization approach is utilized. The numerical example is solved with ε-constraint exact method, and this case illustrates the specific process of goods distribution, the relationship between objectives, and the sensitivity analysis of uncertainties. For the large-size forms, two heuristic algorithms are proposed and the efficiency of the proposed algorithms is assessed.
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title_short	A Multi-Objective Robust Optimization Design for Grid Emergency Goods Distribution Under Mixed Uncertainty
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