Longyue Li¹, Guoqing Zhang¹, Bo Cao¹, Shuqi Wang², Ye Tian^1,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-26, 2026, DOI:10.32604/cmc.2025.070622 - 09 December 2025

Abstract Modern battlefields exhibit high dynamism, where traditional static weighting methods in combat effectiveness assessment fail to capture real-time changes in indicator values, leading to limited assessment accuracy—especially critical in scenarios like sudden electronic warfare or degraded command, where static weights cannot reflect the operational value decay or surge of key indicators. To address this issue, this study proposes a dynamic adaptive weighting method for evaluation indicators based on G1-CRITIC-PIVW. First, the G1 (Sequential Relationship Analysis Method) subjective weighting method—translates expert knowledge into indicator importance rankings—leverages expert knowledge to quantify the relative importance of indicators via… More >

Khadija Slimani^1,2,*, Samira Khoulji², Hamed Taherdoost^3,4, Mohamed Larbi Kerkeb⁵

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4667-4686, 2025, DOI:10.32604/cmc.2025.070173 - 23 October 2025

Abstract The integration of the dynamic adaptive routing (DAR) algorithm in unmanned aerial vehicle (UAV) networks offers a significant advancement in addressing the challenges posed by next-generation communication systems like 6G. DAR’s innovative framework incorporates real-time path adjustments, energy-aware routing, and predictive models, optimizing reliability, latency, and energy efficiency in UAV operations. This study demonstrated DAR’s superior performance in dynamic, large-scale environments, proving its adaptability and scalability for real-time applications. As 6G networks evolve, challenges such as bandwidth demands, global spectrum management, security vulnerabilities, and financial feasibility become prominent. DAR aligns with these demands by offering More >

Khadija Slimani^1,2,*, Samira Khoulji², Hamed Taherdoost^3,4, Mohamed Larbi Kerkeb⁵

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 4115-4132, 2025, DOI:10.32604/cmc.2025.066544 - 23 September 2025

Abstract Reliable and efficient communication is essential for Unmanned Aerial Vehicle (UAV) networks, especially in dynamic and resource-constrained environments such as disaster management, surveillance, and environmental monitoring. Frequent topology changes, high mobility, and limited energy availability pose significant challenges to maintaining stable and high-performance routing. Traditional routing protocols, such as Ad hoc On-Demand Distance Vector (AODV), Load-Balanced Optimized Predictive Ad hoc Routing (LB-OPAR), and Destination-Sequenced Distance Vector (DSDV), often experience performance degradation under such conditions. To address these limitations, this study evaluates the effectiveness of Dynamic Adaptive Routing (DAR), a protocol designed to adapt routing decisions… More >

Zhenyu Yan^1,*, Haotian Bian²

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2241-2257, 2023, DOI:10.32604/csse.2023.040603 - 28 July 2023

Abstract As millimeter waves will be widely used in the Internet of Things (IoT) and Telematics to provide high bandwidth communication and mass connectivity, the coverage optimization of base stations can effectively improve the quality of communication services. How to optimize the convergence speed of the base station coverage solution is crucial for IoT service providers. This paper proposes the Muti-Fusion Sparrow Search Algorithm (MFSSA) optimize the situation to address the problem of discrete coverage maximization and rapid convergence. Firstly, the initial swarm diversity is enriched using a sine chaotic map, and dynamic adaptive weighting is… More >

Mutasem K. Alsmadi^1,*, Ghaith M. Jaradat², Malek Alzaqebah³, Ibrahim ALmarashdeh¹, Fahad A. Alghamdi¹, Rami Mustafa A. Mohammad⁴, Nahier Aldhafferi⁴, Abdullah Alqahtani⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1995-2014, 2022, DOI:10.32604/cmc.2022.025077 - 24 February 2022

Abstract Timetabling problem is among the most difficult operational tasks and is an important step in raising industrial productivity, capability, and capacity. Such tasks are usually tackled using metaheuristics techniques that provide an intelligent way of suggesting solutions or decision-making. Swarm intelligence techniques including Particle Swarm Optimization (PSO) have proved to be effective examples. Different recent experiments showed that the PSO algorithm is reliable for timetabling in many applications such as educational and personnel timetabling, machine scheduling, etc. However, having an optimal solution is extremely challenging but having a sub-optimal solution using heuristics or metaheuristics is… More >

K. Gayathri Devi^*, R. S. Mishra, A. K. Madan

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 429-448, 2022, DOI:10.32604/iasc.2022.019330 - 03 September 2021

Abstract An NP-hard problem like Flexible Job Shop Scheduling (FJSP) tends to be more complex and requires more computational effort to optimize the objectives with contradictory measures. This paper aims to address the FJSP problem with combined and contradictory objectives, like minimization of make-span, maximum workload, and total workload. This paper proposes ‘Hybrid Adaptive Firefly Algorithm’ (HAdFA), a new enhanced version of the classic Firefly Algorithm (FA) embedded with adaptive parameters to optimize the multi objectives concurrently. The proposed algorithm has adopted two adaptive strategies, i.e., an adaptive randomization parameter (α) and an effective heterogeneous update More >