Operation Loop-Based Optimization Model for Resource Allocation to Military Countermeasures versus Probabilistic Threat

Abstract

Weapons development planning is an unstructured and complex multi-criteria decisionmaking problem, especially in antagonistic environments. In this paper, the defender's decision was modelled as a high complexity non-linear optimization problem with limited resources. An operation loop with realistic link rules was first proposed to model the cooperation relationships among weapons in the defense system. The system dynamics principle was used to characterize the dynamic behavior of the nodes in a complex weapons network. Then, we used cumulative threat and development risk to measure different planning solutions by considering the opponent and uncertainties in the development process. Next, an improved Differential Evolution (DE) and Non-Dominated Sorting Differential Evolution (NSDE) were designed to determine the optimal planning solutions for a single objective and multi-objective. The compromise solution, based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), was used to evaluate the Pareto solution set of the multi-objective. Finally, an illustrative case was studied to verify the feasibility and validity of the proposed model.

Development of a Generic Decision Tree for the Integration of Multi-Criteria Decision-Making (MCDM) and Multi-Objective Optimization (MOO) Methods under Uncertainty to Facilitate Sustainability Assessment: A Methodical Review

“…Xu et al [79] and Sharma and Mukherjee [80] proposed improved NSGA-II methods. Wan et al [81] integrated NSGA-II with differential evolution and named the method Non-dominated Sorting Differential Evolution (NSDE). NSGA-II was selected by the researchers mainly due to its computational speed and better performance in terms of maintaining the diversity/versatility among Pareto-optimal solutions, and better convergence efficiency [2,79,[82][83][84].…”

Bibliometric Studies on Multi-Criteria Decision Analysis (Mcda) Methods Applied in Military Problems

“…Another MCDA method widely used in military problems is the Technique for Order Preferences by Similarity To Ideal Solution (TOPSIS), as noted in the classification of the threat of military targets (Zhang et al, 2012); risk management for obsolescence in the U.S. Armed Forces (Adetunji et al, 2018); target-tracked prioritization to surveille ballistic missiles (Luo & Li, 2009); evaluating initial training aircraft (Wang & Chang, 2007), abrasive Water Jet machining of military-grade armor steel (Rammohan et al, 2021), method of air force attack airline (Chen & Zhang, 2016); scheduling algorithm based on heterogeneity and confidence for mimic defense (Zhang et al, 2020); resource allocation to military countermeasures versus probabilistic threat (Wan et al, 2018); supplier selection and evaluation in military supply chain and order allocation (Nazeri et al, 2019).…”

A Multi-Objective INLP Model of Sustainable Resource Allocation for Long-Range Maritime Search and Rescue

“…NSGA-II is a popular multi-objective evolutionary algorithm (MOEA), which uses non-dominated sorting and shares variable methods to maintain the diversity of Pareto frontiers effectively, and it has been proven to be effective in solving two objective problems [22,23]. The implementation is based on the MOEA Framework (http://moeaframework.org/), which is a free and open source Java library for developing and experimenting with MOEAs.…”