This paper introduces a novel population-based bio-inspired meta-heuristic optimization algorithm, called Blood Coagulation Algorithm (BCA). BCA derives inspiration from the process of blood coagulation in the human body. The underlying concepts and...
This paper describes a unique meta-heuristic technique for hybridizing bio-inspired heuristic algorithms. The technique is based on altering the state of agents using a logistic probability function that is dependent on an agent’s fitness rank....
Hyper-heuristics are widely used for solving numerous complex computational search problems because of their intrinsic capability to generalize across problem domains. The fair-share iterated local search is one of the most successful hyper-heuristic...
Global optimization, especially on a large scale, is challenging to solve due to its nonlinearity and multimodality. In this paper, in order to enhance the global searching ability of the firefly algorithm (FA) inspired by bionics, a novel hybrid met...
This paper introduces the election optimization algorithm (EOA), a meta-heuristic approach for engineering optimization problems. Inspired by the democratic electoral system, focusing on the presidential election, EOA emulates the complete election p...
The charging loads of electric vehicles (EVs) at residential premises are controlled through a tariff system based on fixed timing. The conventional tariff system presents the herding issue, such as with many connected EVs, all of them are directed t...
This study introduces the Morabaraba Optimization Algorithm (MOA), a new global optimization method derived from the sequential and strategic dynamics of the traditional Morabaraba board game. The algorithm translates the main stages of the game into...
This paper presents a comprehensive survey of the meta-heuristic optimization algorithms on the text clustering applications and highlights its main procedures. These Artificial Intelligence (AI) algorithms are recognized as promising swarm intellige...
The fragmentation of vessel tracks represents a significant challenge in the context of high-frequency surface wave radar (HFSWR) tracking. This paper proposes a new track segment association (TSA) algorithm that integrates optimal tracklet assignmen...
This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heu...
Unmanned Aerial Vehicles (UAVs), a subset of aerial robots, play crucial roles in various domains, such as disaster management, agriculture, and healthcare. Their application proves invaluable in situations where human intervention poses risks or inv...
Combined heat and power (CHP) plants are known as efficient technologies to reduce environmental emissions, balance energy costs, and increase total energy efficiency. To obtain a more efficient system, various optimization methods have been employed...
A tapered concrete-filled double-skin steel tubular (TCFDST) structure has been used as the main framework in transmission towers, offshore facility platforms, and turbine towers owing to its excellent mechanical properties. In order to solve the dif...
Human–robot collaborative assembly line balancing and scheduling constitutes an NP-hard combinatorial optimization problem involving the simultaneous optimization of task assignment, resource allocation, processing mode selection, station-level...
Path planning, as the core of navigation control for mobile robots, has become the focus of research in the field of mobile robots. Various path planning algorithms have been recently proposed. In this paper, in view of the advantages and disadvantag...
This paper presents a novel composite heuristic algorithm for global optimization by organically integrating the merits of a water cycle algorithm (WCA) and gravitational search algorithm (GSA). To effectively reinforce the exploration and exploitati...
Green supply chain management is critical for driving sustainable development and addressing escalating environmental challenges faced by companies. However, due to the multidimensionality of cost–benefit analysis and the intricacies of supply...
Numerous network cyberattacks have been launched due to inherent weaknesses. Network intrusion detection is a crucial foundation of the cybersecurity field. Intrusion detection systems (IDSs) are a type of machine learning (ML) software proposed for...
In recent years, demand side management (DSM) techniques have been designed for residential, industrial and commercial sectors. These techniques are very effective in flattening the load profile of customers in grid area networks. In this paper, a he...
Swarm intelligence optimization methods have steadily gained popularity as a solution to multi-objective optimization issues in recent years. Their study has garnered a lot of attention since multi-objective optimization problems have a hard high-dim...
To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs) have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a chargi...
The budgeted influence maximization (BIM) problem aims to select an optimal subset of nodes, each with a unique selection cost, to maximize the influence in a network under a fixed budget. Most existing methods address static networks with constant n...
As exact algorithms are unfeasible to solve real optimization problems, due to their computational complexity, meta-heuristics are usually used to solve them. However, choosing a meta-heuristic to solve a particular optimization problem is a non-triv...
Mapping optimization of network-on-chips (NoCs) for specific applications has become one of the most important keys of the SoC top-level design. However, the topology of NoC applied is usually regular topology, such as mesh, torus, etc., which may ge...
Aiming at the accurate prediction of the inception of instability in a compressor, a dynamic system stability model is proposed based on a sparrow-inspired meta-heuristic optimization algorithm in this article. To achieve this goal, a spatial mode is...
The cavity haloscope is among the most widely adopted experimental platforms designed to detect dark matter axions with its principle relying on the conversion of axions into microwave photons in the presence of a strong magnetic field. The Josephson...
In the proposed article, we present a nature-inspired optimization algorithm, which we called Polar Bear Optimization Algorithm (PBO). The inspiration to develop the algorithm comes from the way polar bears hunt to survive in harsh arctic conditions....
In response to the increasing demands for energy conservation and pollution reduction, optimizing transformer design to reduce operational losses and minimize raw material usage has become crucial. This paper introduces an innovative methodology that...
Association rule mining (ARM) is one of the core techniques of data mining to discover potentially valuable association relationships from mixed datasets. In the current research, various heuristic algorithms have been introduced into ARM to address...
Phosphorus (P) is the most important substance in inorganic fertilizers used in the agriculture industry. In this study, a multi-product and multi-objective model is presented considering economic and environmental concerns to design a renewable and...
In this paper, a new hybrid algorithm based on two meta-heuristic algorithms is presented to improve the optimization capability of original algorithms. This hybrid algorithm is realized by the deep ensemble of two new proposed meta-heuristic methods...
This study addresses the challenge of accurately correlating detailed and reduced thermal models in aerospace applications by using heuristic global optimization methods. In the context of increasingly complex thermal systems, traditional manual corr...
The fourth industrial revolution and the digital transformation of consumer markets require contemporary manufacturers to rethink and reshape their business models to deal with the ever-changing customer demands and market turbulence. Manufacturers n...
Optimal power flow (OPF), a mathematical programming problem extending power flow relationships, is one of the essential tools in the operation and control of power grids. To name but a few, the primary goals of OPF are to meet system demand at minim...
For 5G and future Internet, in this paper, we propose a task allocation method for future Internet application to reduce the total latency in a mobile edge computing (MEC) platform with three types of servers: a dedicated MEC server, a shared MEC ser...
Quantum optimization has recently drawn considerable attention as one of the possible applications of noisy intermediate-scale quantum computation, yet the problem of qubit requirement remains a major bottleneck when combinatorial optimization proble...
Meta-heuristic algorithms have successfully solved many real-world problems in recent years. Inspired by different natural phenomena, the algorithms with special search mechanisms can be good at tackling certain problems. However, they may fail to so...
The paper presents the process of optimizing the duty cycle of a rotary crane. The minimization of the carried load’s trajectory was chosen as the objective function. The research was conducted using the genetic algorithm and the particle swarm...
Location information is the primary feature of wireless sensor networks, and it is more critical for Mobile Wireless Sensor Networks (MWSN) to monitor specific targets. How to improve the localization accuracy is a challenging problem for researchers...
In this paper, we introduce a new combinatorial optimization problem entitled the color mix problem (CMP), which is a more general case of the grey pattern quadratic assignment problem (GP-QAP). Also, we propose an original hybrid genetic-iterated ta...
This article presents an in-depth analysis of three advanced strategies to tune fractional PID (FOPID) controllers for a nonlinear system of interconnected tanks, simulated using MATLAB. The study focuses on evaluating the performance characteristics...
Optical network-on-chip is considered to be a promising technology to solve the problems of low bandwidth and high latency in the traditional interconnection network. However, due to the inevitable leakage of optical devices, the optical signal will...
This paper presents an energy-management strategy based on a recently introduced Political Optimizer (PO) for a microgrid installation at Wroclaw University of Science and Technology. The aim of the study is to check the effectiveness of two recently...
In this paper, a hybrid gradient simulated annealing algorithm is guided to solve the constrained optimization problem. In trying to solve constrained optimization problems using deterministic, stochastic optimization methods or hybridization between...
This research paper proposes the application of a meta-heuristic algorithm, namely the water cycle algorithm (WCA), for optimizing the performance of a multi-level inverter for a distributed energy resources-based smart grid system. The aim is to fin...
Optimization is a process of minimizing or maximizing a given objective function under specified constraints. In multi-objective optimization (MOO), multiple conflicting functions are optimized within defined criteria. Numerous MOO techniques have be...
The distributed energy system emerges as a promising and valuable technology. However, various factors are hindering the development of the algorithm, including the diversity of units and their respective output constraints. Additionally, the multipl...
In this paper, an improved Beluga Whale Optimization algorithm based on data mining and scheduling rules with AdaBoost(IBWO-DDR-AdaBoost) rule heuristic scheduling method for solving job-shop scheduling problems (JSP) is proposed, in which data minin...
Engineering design optimization in real life is a challenging global optimization problem, and many meta-heuristic algorithms have been proposed to obtain the global best solutions. An excellent meta-heuristic algorithm has two symmetric search capab...
This study proposes a method named Hybrid Heuristic Proximal Policy Optimization (HHPPO) to implement online 3D bin-packing tasks. Some heuristic algorithms for bin-packing and the Proximal Policy Optimization (PPO) algorithm of deep reinforcement le...
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