17 papers · ranked by Valyu relevance
Szilárd Kovács, Csaba Budai, János Botzheim
In this paper, we present the Colonial Bacterial Memetic Algorithm (CBMA), an advanced evolutionary optimization approach for robotic applications. CBMA extends the Bacterial Memetic Algorithm by integrating Cultural Algorithms and co-evolutionary dynamics inspired by bacterial group behavior. This combination of…
Tongzheng Li, Hongchi Meng, Dong Wang, Bin Fu + 3 more
'Zhenzhong Liu' 'Ameer Hamza Khan'] The Slime Mould Algorithm (SMA) is a widely used swarm intelligence algorithm. Encouraged by the theory of no free lunch and the inherent shortcomings of the SMA, this work proposes a new variant of the SMA, called the BWSMA, in which three improvement mechanisms are integrated. The…
Jialing Yan, Gang Hu, Jiulong Zhang, Heming Jia + 2 more
'Xuewen Xia'] To address the shortcomings of the recently proposed Fick’s Law Algorithm, which is prone to local convergence and poor convergence efficiency, we propose a multi-strategy improved Fick’s Law Algorithm (FLAS). The method combines multiple effective strategies, including differential mutation strategy…
Ahmed F. Ali, Mohamed A. Tawhid
Cuckoo search algorithm is a promising metaheuristic population based method. It has been applied to solve many real life problems. In this paper, we propose a new cuckoo search algorithm by combining the cuckoo search algorithm with the Nelder-Mead method in order to solve the integer and minimax optimization…
Fu-Jou Lai, Hong-Tsun Chang, Wei-Sheng Wu
Background Computational identification of cooperative transcription factor (TF) pairs helps understand the combinatorial regulation of gene expression in eukaryotic cells. Many advanced algorithms have been proposed to predict cooperative TF pairs in yeast. However, it is still difficult to conduct a comprehensive and…
Ran Wang, Weiquan Huang, Junyu Wu, Chen Chen + 3 more
To address the rapid population diversity loss and premature convergence of the Artificial Lemming Algorithm (ALA) in complex optimization problems, this paper proposes an Improved Artificial Lemming Algorithm (IALA) with multi-strategy enhancements inspired by lemming behavior. First, a non-uniform mutation operator…
Ali Asghari, Mohammadhossein Mohammadi, Heming Jia
Metaheuristic algorithms are widely used to find optimal or near-optimal solutions for complex problems by taking inspiration from natural behaviors and processes. Although many different methods have been developed, a common problem in many of them is maintaining a good balance between exploration and exploitation and…
Ping Zeng, Qingping Tan, Xiankai Meng, Zeming Shao + 5 more
'Ying Yan' 'Wei Cao' 'Jianjun Xu' 'Francesco Pappalardo'] In this paper, based on our previous multi-pattern uniform resource locator (URL) binary-matching algorithm called HEM, we propose an improved multi-pattern matching algorithm called MH that is based on hash tables and binary tables. The MH algorithm can be…
Syed Hamid Hussain Madni, Muhammad Shafie Abd Latiff, Mohammed Abdullahi, Shafi’i Muhammad Abdulhamid + 2 more
'Mohammed Abdullahi' 'Shafi’i Muhammad Abdulhamid' 'Mohammed Joda Usman' 'Kim-Kwang Raymond Choo'] Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for…
Wei-Sheng Wu, Meng-Jhun Jhou
Background Missing value imputation is important for microarray data analyses because microarray data with missing values would significantly degrade the performance of the downstream analyses. Although many microarray missing value imputation algorithms have been developed, an objective and comprehensive performance…
Bilal Khurshid, Shahid Maqsood, Yahya Khurshid, Khawar Naeem + 1 more
This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. To address the complexity of this NP-hard problem, the HES-IG algorithm combines evolution strategies (ES) and iterated greedy (IG) algorithm, as hybridizing…
Li Zhang, XiaoBo Chen
Feature selection is a critical component of machine learning and data mining to remove redundant and irrelevant features from a dataset. The Chimp Optimization Algorithm (CHoA) is widely applicable to various optimization problems due to its low number of parameters and fast convergence rate. However, CHoA has a weak…
Mohammad Abdur Rob, Md. Zakir Hossen, Md. Kamal Hossen, Md. Mithun Ali + 2 more
Sorting algorithms play a crucial role in computing, but most are designed with rigid structure that are only efficient under certain conditions. Although some sorting algorithms perform well in some circumstances, they do not perform well on some resistant platforms. This study introduces Wall-L Merge Sort, which…
Hannah P. Cowley, Mandy Natter, Karla Gray-Roncal, Rebecca E. Rhodes + 6 more
Rigorous comparisons of human and machine learning algorithm performance on the same task help to support accurate claims about algorithm success rates and advances understanding of their performance relative to that of human performers. In turn, these comparisons are critical for supporting advances in artificial…
Yidi Hao, Baodong Qin, Yitian Sun, Jose Manuel Molina López
Due to the rapid development of machine-learning technology, companies can build complex models to provide prediction or classification services for customers without resources. A large number of related solutions exist to protect the privacy of models and user data. However, these efforts require costly communication…
Morihiro Hayashida, Tatsuya Akutsu
Background Comparison of various kinds of biological data is one of the main problems in bioinformatics and systems biology. Data compression methods have been applied to comparison of large sequence data and protein structure data. Since it is still difficult to compare global structures of large biological networks…
Zhen Shang, Jin-Kao Hao, Fei Ma, Daniele D’Agostino
Product development projects usually contain many interrelated activities with complex information dependences, which induce activity rework, project delay and cost overrun. To reduce negative impacts, scheduling interrelated activities in an appropriate sequence is an important issue for project managers. This study…