Cost-Aware and Energy-Efficient Task Scheduling Based on Grey Wolf Optimizer [PDF]
One of the principal challenges in the cloud is the task scheduling problem. Appropriate task scheduling algorithms are needed to achieve goals such as load balancing, minimum cost, minimum energy consumption, etc.
Reyhane Ghafari, Najme Mansouri
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Advances in meta-heuristic methods for large-scale black-box optimization problems
The optimal design of complex engineering equipment usually faces high-complexity, high-dimensional optimization problems – the so-called "large-scale black-box optimization problems (LBOPs)" – which are characterized by unavailable mathematical ...
Puyu JIANG +3 more
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Comparison of Recent Meta-Heuristic Optimization Algorithms Using Different Benchmark Functions
Meta-heuristic optimization algorithms are used in many application areas to solve optimization problems. In recent years, meta-heuristic optimization algorithms have gained importance over deterministic search algorithms in solving optimization problems.
Mahmut Dirik
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Metaheuristic Algorithms in Optimizing Deep Neural Network Model for Software Effort Estimation
Effort estimation is the most critical activity for the success of overall solution delivery in software engineering projects. In this context, the paper’s main contributions to the literature on software effort estimation are twofold. First, this
Muhammad Sufyan Khan +5 more
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A Hybrid Optimization Framework with Dynamic Transition Scheme for Large-Scale Portfolio Management
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.
Zhenglong Li, Vincent Tam
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A Hybrid Artificial Grasshopper Optimization (HAGOA) Meta-Heuristic Approach: A Hybrid Optimizer For Discover the Global Optimum in Given Search Space [PDF]
Meta-heuristic algorithms are used to get optimal solutions in different engineering branches. Here four types of meta-heuristics algorithms are used such as evolutionary algorithms, swarm-based algorithms, physics based algorithms and human based ...
Brahm Prakash Dahiya +2 more
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Buyer Inspired Meta-Heuristic Optimization Algorithm [PDF]
AbstractNature inspired swarm based meta-heuristic optimization technique is getting considerable attention and established to be very competitive with evolution based and physical based algorithms. This paper proposes a novel Buyer Inspired Meta-heuristic optimization Algorithm (BIMA) inspired form the social behaviour of human being in searching and ...
Debnath Sanjoy +2 more
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The agile earth observation satellite scheduling problem (AEOSSP), as a time-dependent and arduous combinatorial optimization problem, has been intensively studied in the past decades.
Jiawei Chen +4 more
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An Opposition-Based Chaotic Salp Swarm Algorithm for Global Optimization
The salp swarm algorithm (SSA) is a bio-heuristic optimization algorithm proposed in 2017. It has been proved that SSA has competitive results compared to several other well-known meta-heuristic algorithms on various optimization problem.
Xiaoqiang Zhao +3 more
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Eurasian oystercatcher optimiser: New meta-heuristic algorithm [PDF]
AbstractModern optimisation is increasingly relying on meta-heuristic methods. This study presents a new meta-heuristic optimisation algorithm called Eurasian oystercatcher optimiser (EOO). The EOO algorithm mimics food behaviour of Eurasian oystercatcher (EO) in searching for mussels.
Salim Ahmad +3 more
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