A Prospect-Theory-Based Operation Loop Decision-Making Method for Kill Web

In the military field, decision making has become the core of the new operational concept, known as the “kill web”. Although the theory of kill web has been widely recognized by many countries, the decision-making methods for the kill web are still in the early stage. Therefore, there is a need for...

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Main Authors: Luyao Wang, Libin Chen, Zhiwei Yang, Minghao Li, Kewei Yang, Mengjun Li
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/10/19/3486
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author Luyao Wang
Libin Chen
Zhiwei Yang
Minghao Li
Kewei Yang
Mengjun Li
author_facet Luyao Wang
Libin Chen
Zhiwei Yang
Minghao Li
Kewei Yang
Mengjun Li
author_sort Luyao Wang
collection DOAJ
description In the military field, decision making has become the core of the new operational concept, known as the “kill web”. Although the theory of kill web has been widely recognized by many countries, the decision-making methods for the kill web are still in the early stage. Therefore, there is a need for a new decision-making method for the kill web. Firstly, different from the traditional scheme decision, the kill web is a complex system. The method of complex network provides a new perspective on complex systems, so the kill web was modeled based on complex network. Secondly, the kill web relies on artificial intelligence to provide decision-makers with operation loop solutions, and then decision-makers rely on the experience to make a final decision. However, the current decision-making methods only consider one of the intelligent and human decision-making methods, while the kill web needs to consider both. Hence, we combined intelligent decision making with human decision making through multi-objective optimization and the prospect theory. Finally, we designed a nondominated sorting ant colony genetic algorithm-II (NSACGA-II) to solve large-scale problems, since the kill web is a large-scale system. In addition, an illustrative case was used to verify the feasibility and effectiveness of the proposed model. The results showed that, compared with other classical multi-objective optimization algorithms, the NSACGA-II is superior to other superior algorithms in terms of the hypervolume (HV) and spacing (SP), which verifies the effectiveness of the method and greatly improves the quality of commanders’ decision-making.
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spelling doaj.art-aec509d712114dc2a7a08dc0ff2f01952023-11-23T21:02:20ZengMDPI AGMathematics2227-73902022-09-011019348610.3390/math10193486A Prospect-Theory-Based Operation Loop Decision-Making Method for Kill WebLuyao Wang0Libin Chen1Zhiwei Yang2Minghao Li3Kewei Yang4Mengjun Li5College of Systems Engineering, National University of Defense Technology, Changsha 410073, ChinaCollege of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, ChinaCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, ChinaCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, ChinaCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, ChinaIn the military field, decision making has become the core of the new operational concept, known as the “kill web”. Although the theory of kill web has been widely recognized by many countries, the decision-making methods for the kill web are still in the early stage. Therefore, there is a need for a new decision-making method for the kill web. Firstly, different from the traditional scheme decision, the kill web is a complex system. The method of complex network provides a new perspective on complex systems, so the kill web was modeled based on complex network. Secondly, the kill web relies on artificial intelligence to provide decision-makers with operation loop solutions, and then decision-makers rely on the experience to make a final decision. However, the current decision-making methods only consider one of the intelligent and human decision-making methods, while the kill web needs to consider both. Hence, we combined intelligent decision making with human decision making through multi-objective optimization and the prospect theory. Finally, we designed a nondominated sorting ant colony genetic algorithm-II (NSACGA-II) to solve large-scale problems, since the kill web is a large-scale system. In addition, an illustrative case was used to verify the feasibility and effectiveness of the proposed model. The results showed that, compared with other classical multi-objective optimization algorithms, the NSACGA-II is superior to other superior algorithms in terms of the hypervolume (HV) and spacing (SP), which verifies the effectiveness of the method and greatly improves the quality of commanders’ decision-making.https://www.mdpi.com/2227-7390/10/19/3486operation loopkill webcombat decision makingprospect theorydecision preferencemulti-objective optimization
spellingShingle Luyao Wang
Libin Chen
Zhiwei Yang
Minghao Li
Kewei Yang
Mengjun Li
A Prospect-Theory-Based Operation Loop Decision-Making Method for Kill Web
Mathematics
operation loop
kill web
combat decision making
prospect theory
decision preference
multi-objective optimization
title A Prospect-Theory-Based Operation Loop Decision-Making Method for Kill Web
title_full A Prospect-Theory-Based Operation Loop Decision-Making Method for Kill Web
title_fullStr A Prospect-Theory-Based Operation Loop Decision-Making Method for Kill Web
title_full_unstemmed A Prospect-Theory-Based Operation Loop Decision-Making Method for Kill Web
title_short A Prospect-Theory-Based Operation Loop Decision-Making Method for Kill Web
title_sort prospect theory based operation loop decision making method for kill web
topic operation loop
kill web
combat decision making
prospect theory
decision preference
multi-objective optimization
url https://www.mdpi.com/2227-7390/10/19/3486
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