Swarm Intelligence Algorithms for Weapon-Target Assignment in a Multilayer Defense Scenario: A Comparative Study

Abstract

Weapon-target assignment (WTA) is a kind of NP-complete problem in military operations research. To solve the multilayer defense WTA problems when the information about enemy’s attacking plan is symmetric to the defender, we propose four heuristic algorithms based on swarm intelligence with customizations and improvements, including ant colony optimization (ACO), binary particle swarm optimization (BPSO), integer particle swarm optimization (IPSO) and sine cosine algorithm (SCA). Our objective is to assess and compare the performance of different algorithms to determine the best algorithm for practical large-scale WTA problems. The effectiveness and performance of various algorithms are evaluated and compared by means of a benchmark problem with a small scale, the theoretical optimal solution of which is known. The four algorithms can obtain satisfactory solutions to the benchmark problem with high quality and high robustness, while IPSO is superior to BPSO, ACO and SCA with respect to the solution quality, algorithmic robustness and computational efficiency. Then, IPSO is applied to a large-scale WTA problem, and its effectiveness and performance are further assessed. We demonstrate that IPSO is capable of solving large-scale WTA problems with high efficiency, high quality and high robustness, thus meeting the critical requirements of real-time decision-making in modern warfare.

Applications and Evaluations ofBio-InspiredApproaches in Cloud Security: A Review

“…Finally, we would like to suggest some of the possible scopes, shortly for researcher and practitioner as a brainstorming concept: reducing the reaction time and maximizing VM's resource allocation considering the QoS factor; improving the load stability in WSN using RCNN learning; SVM-PSO based community Forensics and RNN techniques for Intrusion Detection. Feature selection from natural algorithm Koroniotis et al [133] Quality of service NF PSO and DL Enhance NF Al hawaitat et al [134] WS PNS PSO Jamming attack Shi et al [135] Anomaly detection P ADAID 1 Presented unsupervised clustering Usman et al [96] VM allocation VR EFPA 2 Energy-oriented allocation Singh et al [103] VM migration VR HBGA 3 Energy reduction Naik et al [130] VM allocation VR Fruit fly Reduce host migration Meng & Pan [136] Optimization VR FFOA solve MKP 4 Mosa & Paton [126] VM placement VR GA Reduce response time & maximize resources utilization Duan et al [137] Information leakage P DL Protect server Festag & Spreckelsen [138] Data leakage P DL Detection of protected health information Chari et al [125] Quality of service IA DL Generate password via cognitive information Li et al [139] Signal processing IA GA Feature extraction via EEG signal Saini & Kansal [127] WSN ACS SI Reduce energy consumption and increase network life time Chen et al [140] Biometric identification IA CNN Proposed GSLT-CNN using human brain EEG Cao & Fang [141] Multilayer defense scenario ACS SI Found proficient IPSO elucidating extensive WTA problem Aliyu et al [124] Resource allocation ACS Ant colony Illustrated faster convergence optimize makespan time Poonia [142] VAN ACS SI Found significant difference in VANET routing protocol and Swarm based protocol Verma et al [ [129] Feature extraction ID GA Reduce features to classify network packet Tan et al [148] Real time network attack intrusion ID NN Able to detect in network precisely…”

A Novel Elitism Co-Evolutionary Algorithm for Antagonistic Weapon-Target Assignment

“…Based on the framework of the co-evolutionary algorithm, the ECO-AGWTA algorithm is proposed to solve the model shown in equation (17). In this algorithm, the red and blue sides are represented by two independent populations, which are evolved simultaneously.…”

“…Therefore, for the DWTA problem, the distribution of weapons in the previous stage will have an impact on the later stage. In addition, for different combat tasks, each type of WTA also includes resource-oriented problems [14][15][16][17] and target-oriented problems [18][19][20].…”

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

“…In WTA problems, model constraints are usually used as algorithm termination conditions. In the model constraints (22), the constraint of marginal return expectation of a weapon is proposed. This constraint not only optimizes the decision efficiency-cost ratio but also controls the algorithm flow adaptively.…”

“…The WTA problem is proved to be NP-complete, and the objective function is convex [20]. The exact algorithms solving the WTA model have a "dimension explosion" dilemma, which does not satisfy the real-time requirements in practical applications [21,22]. Hence, the alternate approaches, such as model transformation, heuristics algorithm, are studied to approximate the optimal solution [23][24][25].…”