Results 11 to 20 of about 75,020 (311)
Heuristic backtracking algorithms for SAT [PDF]
In recent years backtrack search SAT solvers have been the subject of dramatic improvements. These improvements allowed SAT solvers to successfully replace BDDs in many areas of formal verification, and also motivated the development of many new challenging problem instances, many of which too hard for the current generation of SAT solvers. As a result,
Ateet Bhalla +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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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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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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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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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.
Robertas Damaševičius +1 more
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A Heuristic for Direct Product Graph Decomposition [PDF]
In this paper we describe a heuristic for decomposing a directed graph into factors according to the direct product (also known as Kronecker, cardinal or tensor product). Given a directed, unweighted graph G with adjacency matrix Adj(G), our heuristic
Moreno Marzolla +2 more
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Combinatorial Dominance Guarantees for Heuristic Algorithms [PDF]
An $f(n)$ $\textit{dominance bound}$ on a heuristic for some problem is a guarantee that the heuristic always returns a solution not worse than at least $f(n)$ solutions.
Daniel Berend +2 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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