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Metaheuristic algorithm
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This paper proposes an improvement for two heuristic algorithms, PD-Steiner and SPT-Steiner, to solve a SMT problem in large size sparse graphs with edge weights not exceeding 10, and validates this proposal on large-size sparse graphs up to 100000 vertices. These experimental results are useful information for further research on the SMT problem.
10p
visystrom
22-11-2023
3
3
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In this paper, we survey the approach for solving the maximum clique graph problem in the direction of metaheuristic algorithms and evaluate the quality of these research based on the experimental data system DIMACS. This survey can be useful for further research on maximum clique graph problems.
7p
visystrom
22-11-2023
8
4
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The proposed algorithm utilizes the migration method to identify local extremes and then relocates the population to explore new solution spaces for further evolution. The MIMEM algorithm is evaluated on the iMOPSE benchmark dataset, and the results demonstrate that it outperforms.
8p
visystrom
22-11-2023
8
3
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This paper introduces the application of the standard Particle Swarm Optimization (PSO) algorithm with discrete integer variables to solve the problem of optimizing the position of tower cranes and material supply points.
10p
visharma
20-10-2023
6
3
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Part 1 book "Production scheduling" includes content: Statement of production scheduling, basic concepts and methods in production scheduling, metaheuristics and scheduling; genetic algorithms and scheduling, constraint propagation and scheduling, simulation approach.
182p
oursky03
21-08-2023
9
5
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This study suggests a new metaheuristic algorithm for global optimization, based on parallel hybridizing the swarm optimization (PSO) and Gravitational search algorithm (GSA). Subgroups of the population are formed by dividing the swarm’s community. Communication between the subsets can be developed by adding strategies for the mutation. Twenty-three benchmark functions are used to test its performance to verify the feasibility of the proposed algorithm.
11p
linyanjun_2408
21-04-2022
19
3
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This study suggests a solution to the ELD problem based on a new intelligent optimization algorithm called the Jellyfish search algorithm (JSA). Due to the imitation of jellyfish's behavior searching for food in the ocean, the JSA owes the advanced characteristics, e.g., simple structure, fast search, and easy to implement. The ELD problem is mathematically expressed as a typical multi-constraint nonlinear optimization problem that can be dealt with by optimizing the JSA algorithm successfully.
10p
linyanjun_2408
21-04-2022
17
3
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Metaheuristic search algorithms are used to develop new protocols for optimal intravenous insulin infusion rate recommendations in scenarios involving hospital in-patients with Type 1 Diabetes. Two metaheuristic search algorithms are used, namely, Particle Swarm Optimization and Covariance Matrix Adaption Evolution Strategy.
28p
redemption
20-12-2021
14
0
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This study used 1,538 data samples from Goldman Osteometric Dataset which consisted of femur, humerus and tibia parts. Based on the feature selection results, the Optimized BPNN outperformed other methods for all datasets.
27p
spiritedaway36
28-11-2021
14
2
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The performance measures were described in terms of mean squared errors, classification accuracies, sensitivities, specificities, the area under the curve, and receiver operating characteristic curve. It was found that IMGWO outperformed three popular metaheuristic approaches including GWO, genetic algorithm, and particle swarm optimization. Results confirmed the potency of IMGWO as a viable learning technique for an ANN
36p
spiritedaway36
28-11-2021
6
1
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This paper deals with the Traveling Salesman Problem with Multi-Visit Drone (TSPMVD) in which a truck works in collaboration with a drone that can serve up to q ≥ 1 customers consecutively during each sortie. We propose a Mixed Integer Linear Programming (MILP) formulation and a metaheuristic based on Iterated Local Search (ILS) to solve the problem. Benchmark instances collected from the literature of the special case with q = 1 are used to test the performance of our algorithms.
29p
spiritedaway36
25-11-2021
8
2
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This study develops an advanced tool for tackling constrained optimization problems based on an integration of feasibility rules and differential evolution metaheuristic. This tool aims at finding a solution with the most desired objective function value and concurrently satisfies all of the problem constraints. The optimization approach, named as feasibility rule based differential evolution (FRB-DE), has been developed in Microsoft Visual Studio with C# programming language. The newly developed tool has been tested with two optimization tasks in the field of civil engineering.
6p
nguaconbaynhay12
01-06-2021
18
1
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In this paper, Resource-Constrained Deliveryman Problem (RCDMP) is introduced. The RCDMP problem deals with finding a tour with minimum waiting time sum so that it consumes not more than
10p
nguaconbaynhay11
16-04-2021
17
1
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The Multi-stripe Travelling Salesman Problem (Ms-TSP) is an extension of the Travelling Salesman Problem (TSP). In the q-stripe TSP with q ≥ 1, the objective function sums the costs for traveling from one vertex to each of the next q vertices along the tour. To solve medium to large-sized instances, a metaheuristic approach is proposed. The proposed method has two main components, which are construction and improvement phases. The construction phase generates an initial solution using the Greedy Randomized Adaptive Search Procedure (GRASP).
18p
nguathienthan9
08-12-2020
13
2
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In this article, two new metaheuristic optimization techniques, namely, crow search algorithm and re y algorithm are applied to the well placement optimization problem and their applications to maximize the net pro t value are studied. To study the performance of the re y and crow search algorithm, Eclipse and MATLAB environment are used . The proposed techniques are compared to popular established methods for optimizing well placement. Results show that the re y algorithm is proved to be e cient and e ective compared to other established techniques.
15p
nguathienthan9
08-12-2020
14
0
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This study aims at developing a metaheuristic based image thresholding method via the employments of the HistoryBased Adaptive Differential Evolution with Linear population size reduction algorithm (LSHADE) and the Otsu objective function. The LSHADE algorithm is used to determine an appropriate set of threshold levels that maximizes the separation between clusters of pixels. Experimental results with four applications demonstrate the usefulness of the newly developed tool.
5p
caygaocaolon8
07-11-2020
10
1
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Giải thuật tham lam (tiếng Anh: Greedy algorithm) là một thuật toán giải quyết một bài toán theo kiểu metaheuristic để tìm kiếm lựa chọn tối ưu địa phương ở mỗi bước đi với hy vọng tìm được tối ưu toàn cục. Mời các bạn cùng tham khảo.
24p
tamynhan7
10-10-2020
52
5
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This paper aims to develop a mathematical modeling for Home Health Care Routing and Scheduling Problem and to solve it by means of Simulated Annealing (SA) algorithm considering real condition (staff vehicle traveling, conditions of patients and so forth).
14p
kelseynguyen
27-05-2020
12
2
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This paper develops a hybrid metaheuristic algorithm based on the Genetic Algorithm. In the developed algorithm, (1) a heuristic, (2) a local search, and (3) a restart phase is proposed.
24p
tocectocec
24-05-2020
17
3
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In this study, after presenting a complete definition of the uncapacitated multiple allocation p-hub center problem (UMApHCP) two well-known metaheuristic algorithms are proposed to solve the problem for small scale and large scale standard data sets.
14p
toritori
11-05-2020
8
0
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