Manuel J. C. S. Reis^*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3023-3039, 2025, DOI:10.32604/cmc.2025.066390 - 23 September 2025

Abstract The Vehicle Routing Problem with Time Windows (VRPTW) presents a significant challenge in combinatorial optimization, especially under real-world uncertainties such as variable travel times, service durations, and dynamic customer demands. These uncertainties make traditional deterministic models inadequate, often leading to suboptimal or infeasible solutions. To address these challenges, this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms (GA) with Local Search (LS), while incorporating stochastic uncertainty modeling through probabilistic travel times. The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance. This adaptivity enhances the algorithm’s… More >

Abeer Bashab¹, Ashraf Osman Ibrahim^2,*, Ibrahim Abakar Tarigo Hashem³, Karan Aggarwal⁴, Fadhil Mukhlif⁵, Fuad A. Ghaleb⁵, Abdelzahir Abdelmaboud⁶

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6461-6484, 2023, DOI:10.32604/cmc.2023.034051 - 28 December 2022

Abstract University timetabling problems are a yearly challenging task and are faced repeatedly each semester. The problems are considered non-polynomial time (NP) and combinatorial optimization problems (COP), which means that they can be solved through optimization algorithms to produce the aspired optimal timetable. Several techniques have been used to solve university timetabling problems, and most of them use optimization techniques. This paper provides a comprehensive review of the most recent studies dealing with concepts, methodologies, optimization, benchmarks, and open issues of university timetabling problems. The comprehensive review starts by presenting the essence of university timetabling as… More >

Dan Zhang¹, Yiwen Liang^1,*, Hongbin Dong²

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2025-2045, 2023, DOI:10.32604/cmes.2023.022864 - 23 November 2022

Abstract The artificial immune system, an excellent prototype for developing Machine Learning, is inspired by the function of the powerful natural immune system. As one of the prevalent classifiers, the Dendritic Cell Algorithm (DCA) has been widely used to solve binary problems in the real world. The classification of DCA depends on a data pre-processing procedure to generate input signals, where feature selection and signal categorization are the main work. However, the results of these studies also show that the signal generation of DCA is relatively weak, and all of them utilized a filter strategy to… More > Graphic Abstract

Jingbo Zhang, Yanjun Zhang, Xingjuan Cai^*, Liping Xie^*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 293-316, 2023, DOI:10.32604/cmes.2022.020426 - 24 August 2022

Abstract Compressed sensing (CS), as an efficient data transmission method, has achieved great success in the field of data transmission such as image, video and text. It can robustly recover signals from fewer Measurements, effectively alleviating the bandwidth pressure during data transmission. However, CS has many shortcomings in the transmission of hyperspectral image (HSI) data. This work aims to consider the application of CS in the transmission of hyperspectral image (HSI) data, and provides a feasible research scheme for CS of HSI data. HSI has rich spectral information and spatial information in bands, which can reflect… More >

Abdul Manan¹, Shahida Bashir¹, Abdul Majid^2,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 701-717, 2022, DOI:10.32604/cmc.2022.027064 - 18 May 2022

Abstract The minimum vertex cover problem (MVCP) is a well-known combinatorial optimization problem of graph theory. The MVCP is an NP (nondeterministic polynomial) complete problem and it has an exponential growing complexity with respect to the size of a graph. No algorithm exits till date that can exactly solve the problem in a deterministic polynomial time scale. However, several algorithms are proposed that solve the problem approximately in a short polynomial time scale. Such algorithms are useful for large size graphs, for which exact solution of MVCP is impossible with current computational resources. The MVCP has… More >

Ali Abdullah Hassan^1,*, Salwani Abdullah¹, Kamal Z. Zamli², Rozilawati Razali¹

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2057-2077, 2022, DOI:10.32604/cmc.2022.026310 - 18 May 2022

Abstract Much of our daily tasks have been computerized by machines and sensors communicating with each other in real-time. There is a reasonable risk that something could go wrong because there are a lot of sensors producing a lot of data. Combinatorial testing (CT) can be used in this case to reduce risks and ensure conformance to specifications. Numerous existing meta-heuristic-based solutions aim to assist the test suite generation for combinatorial testing, also known as t-way testing (where t indicates the interaction strength), viewed as an optimization problem. Much previous research, while helpful, only investigated a small… More >

Wenjun Li¹, Siyang Zhang¹, Guangwei Wu², Aldosary Saad³, Amr Tolba^3,4, Gwang-jun Kim^5,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4215-4231, 2022, DOI:10.32604/cmc.2022.024204 - 21 April 2022

Abstract Recently, the development of Industrial Internet of Things has taken the advantage of 5G network to be more powerful and more intelligent. However, the upgrading of 5G network will cause a variety of issues increase, one of them is the increased cost of coverage. In this paper, we propose a sustainable wireless sensor networks system, which avoids the problems brought by 5G network system to some extent. In this system, deploying relays and selecting routing are for the sake of communication and charging. The main aim is to minimize the total energy-cost of communication under More >

Mohammed Hadwan^1,2,3,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5545-5559, 2022, DOI:10.32604/cmc.2022.024512 - 14 January 2022

Abstract A real-life problem is the rostering of nurses at hospitals. It is a famous nondeterministic, polynomial time (NP) -hard combinatorial optimization problem. Handling the real-world nurse rostering problem (NRP) constraints in distributing workload equally between available nurses is still a difficult task to achieve. The international shortage of nurses, in addition to the spread of COVID-19, has made it more difficult to provide convenient rosters for nurses. Based on the literature, heuristic-based methods are the most commonly used methods to solve the NRP due to its computational complexity, especially for large rosters. Heuristic-based algorithms in… More >

Broderick Crawford^1,*, Ricardo Soto¹, Hanns de la Fuente Mella¹, Claudio Elortegui¹, Wenceslao Palma¹, Claudio Torres-Rojas¹, Claudia Vasconcellos-Gaete², Marcelo Becerra¹, Javier Peña¹, Sanjay Misra³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4295-4318, 2022, DOI:10.32604/cmc.2022.023068 - 14 January 2022

Abstract Currently, the industry is experiencing an exponential increase in dealing with binary-based combinatorial problems. In this sense, metaheuristics have been a common trend in the field in order to design approaches to solve them successfully. Thus, a well-known strategy consists in the use of algorithms based on discrete swarms transformed to perform in binary environments. Following the No Free Lunch theorem, we are interested in testing the performance of the Fruit Fly Algorithm, this is a bio-inspired metaheuristic for deducing global optimization in continuous spaces, based on the foraging behavior of the fruit fly, which… More >

Siti Julia Rosli^1,2, Hasliza A Rahim^1,2,*, Khairul Najmy Abdul Rani^1,2, Ruzelita Ngadiran^2,3, Wan Azani Mustafa^3,4, Muzammil Jusoh^1,2, Mohd Najib Mohd Yasin^1,2, Thennarasan Sabapathy^1,2, Mohamedfareq Abdulmalek⁵, Wan Suryani Firuz Wan Ariffin², Ahmed Alkhayyat⁶

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3533-3556, 2022, DOI:10.32604/cmc.2022.021719 - 07 December 2021

Abstract The essential purpose of radar is to detect a target of interest and provide information concerning the target's location, motion, size, and other parameters. The knowledge about the pulse trains’ properties shows that a class of signals is mainly well suited to digital processing of increasing practical importance. A low autocorrelation binary sequence (LABS) is a complex combinatorial problem. The main problems of LABS are low Merit Factor (MF) and shorter length sequences. Besides, the maximum possible MF equals 12.3248 as infinity length is unable to be achieved. Therefore, this study implemented two techniques to… More >