Efficient Decision Approaches for Asset-Based Dynamic Weapon Target Assignment by a Receding Horizon and Marginal Return Heuristic

Efficient Decision Approaches for Asset-Based Dynamic Weapon Target Assignment by a Receding Horizon and Marginal Return Heuristic

The weapon-target assignment problem is a crucial decision support in a Command and Control system. As a typical operational scenario, the major asset-based dynamic weapon target assignment (A-DWTA) models and solving algorithms are challenging to reflect the actual requirement of decision maker. De...

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Bibliographic Details
Main Authors: Kai Zhang, Deyun Zhou, Zhen Yang, Yiyang Zhao, Weiren Kong
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Electronics
Subjects:
weapon target assignment
OODA
heuristic algorithm
combinatorial optimization
decision support system
Online Access:https://www.mdpi.com/2079-9292/9/9/1511
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spelling doaj-10b008c20a4545839be12e39d04218c02020-11-25T01:25:59ZengMDPI AGElectronics2079-92922020-09-0191511151110.3390/electronics9091511Efficient Decision Approaches for Asset-Based Dynamic Weapon Target Assignment by a Receding Horizon and Marginal Return HeuristicKai Zhang0Deyun Zhou1Zhen Yang2Yiyang Zhao3Weiren Kong4School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, ChinaThe weapon-target assignment problem is a crucial decision support in a Command and Control system. As a typical operational scenario, the major asset-based dynamic weapon target assignment (A-DWTA) models and solving algorithms are challenging to reflect the actual requirement of decision maker. Deriving from the “shoot–look–shoot” principle, an “observe–orient–decide–act” loop model for A-DWTA (OODA/A-DWTA) is established. Focus on the decide phase of the OODA/A-DWTA loop, a novel A-DWTA model, which is based on the receding horizon decomposition strategy (A-DWTA/RH), is established. To solve the A-DWTA/RH efficiently, a heuristic algorithm based on statistical marginal return (HA-SMR) is designed, which proposes a reverse hierarchical idea of “asset value-target selected-weapon decision.” Experimental results show that HA-SMR solving A-DWTA/RH has advantages of real-time and robustness. The obtained decision plan can fulfill the operational mission in the fewer stages and the “radical-conservative” degree can be adjusted adaptively by parameters.https://www.mdpi.com/2079-9292/9/9/1511weapon target assignmentOODAheuristic algorithmcombinatorial optimizationdecision support system
collection DOAJ
language English
format Article
sources DOAJ
author Kai Zhang
Deyun Zhou
Zhen Yang
Yiyang Zhao
Weiren Kong
spellingShingle Kai Zhang
Deyun Zhou
Zhen Yang
Yiyang Zhao
Weiren Kong
Efficient Decision Approaches for Asset-Based Dynamic Weapon Target Assignment by a Receding Horizon and Marginal Return Heuristic
Electronics
weapon target assignment
OODA
heuristic algorithm
combinatorial optimization
decision support system
author_facet Kai Zhang
Deyun Zhou
Zhen Yang
Yiyang Zhao
Weiren Kong
author_sort Kai Zhang
title Efficient Decision Approaches for Asset-Based Dynamic Weapon Target Assignment by a Receding Horizon and Marginal Return Heuristic
title_short Efficient Decision Approaches for Asset-Based Dynamic Weapon Target Assignment by a Receding Horizon and Marginal Return Heuristic
title_full Efficient Decision Approaches for Asset-Based Dynamic Weapon Target Assignment by a Receding Horizon and Marginal Return Heuristic
title_fullStr Efficient Decision Approaches for Asset-Based Dynamic Weapon Target Assignment by a Receding Horizon and Marginal Return Heuristic
title_full_unstemmed Efficient Decision Approaches for Asset-Based Dynamic Weapon Target Assignment by a Receding Horizon and Marginal Return Heuristic
title_sort efficient decision approaches for asset-based dynamic weapon target assignment by a receding horizon and marginal return heuristic
publisher MDPI AG
series Electronics
issn 2079-9292
publishDate 2020-09-01
description The weapon-target assignment problem is a crucial decision support in a Command and Control system. As a typical operational scenario, the major asset-based dynamic weapon target assignment (A-DWTA) models and solving algorithms are challenging to reflect the actual requirement of decision maker. Deriving from the “shoot–look–shoot” principle, an “observe–orient–decide–act” loop model for A-DWTA (OODA/A-DWTA) is established. Focus on the decide phase of the OODA/A-DWTA loop, a novel A-DWTA model, which is based on the receding horizon decomposition strategy (A-DWTA/RH), is established. To solve the A-DWTA/RH efficiently, a heuristic algorithm based on statistical marginal return (HA-SMR) is designed, which proposes a reverse hierarchical idea of “asset value-target selected-weapon decision.” Experimental results show that HA-SMR solving A-DWTA/RH has advantages of real-time and robustness. The obtained decision plan can fulfill the operational mission in the fewer stages and the “radical-conservative” degree can be adjusted adaptively by parameters.
topic weapon target assignment
OODA
heuristic algorithm
combinatorial optimization
decision support system
url https://www.mdpi.com/2079-9292/9/9/1511
work_keys_str_mv AT kaizhang efficientdecisionapproachesforassetbaseddynamicweapontargetassignmentbyarecedinghorizonandmarginalreturnheuristic
AT deyunzhou efficientdecisionapproachesforassetbaseddynamicweapontargetassignmentbyarecedinghorizonandmarginalreturnheuristic
AT zhenyang efficientdecisionapproachesforassetbaseddynamicweapontargetassignmentbyarecedinghorizonandmarginalreturnheuristic
AT yiyangzhao efficientdecisionapproachesforassetbaseddynamicweapontargetassignmentbyarecedinghorizonandmarginalreturnheuristic
AT weirenkong efficientdecisionapproachesforassetbaseddynamicweapontargetassignmentbyarecedinghorizonandmarginalreturnheuristic
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