15-Puzzle Problem Solving with the Artificial Bee Colony Algorithm Based on Pattern Database

Tuncer, Adem

doi:10.3897/jucs.65202

Cited by 5 publications

(5 citation statements)

References 14 publications

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“…Nowadays, metaheuristic optimization algorithms are widely used for solving complex problems [33], [34], [35]. One of the algorithms that have been recently used to obtain non-optimal solutions to the Fifteen Puzzle problems was a metaheuristic algorithm Artificial Bee Colony (ABC) [36]. Here, the BA* algorithm with HH is compared with the ABC algorithm to show that the obtained results of BA* are sufficiently accurate and much nearer to the optimal results.…”

Section: Inadmissible Heuristicsmentioning

confidence: 99%

“…To increase the effectiveness and performance of the heuristic function of the ABC algorithm, three heuristics PDB, MD, and LC were combined. The ABC algorithm was run on 25 randomly generated solvable instances of the Fifteen Puzzle but the algorithm did not produce an optimal solution for any of them and it provided solutions that are far from the optimum [36]. Tuncer [36] argued that the results produced by the ABC algorithm are acceptable even though the solution lengths are far from the optimal solution lengths.…”

Section: Inadmissible Heuristicsmentioning

confidence: 99%

“…The ABC algorithm was run on 25 randomly generated solvable instances of the Fifteen Puzzle but the algorithm did not produce an optimal solution for any of them and it provided solutions that are far from the optimum [36]. Tuncer [36] argued that the results produced by the ABC algorithm are acceptable even though the solution lengths are far from the optimal solution lengths. Furthermore, the difference between the solution costs obtained by the ABC algorithm and the optimal solutions for most of the puzzle instances increase when the puzzle instances require more moves to optimally reach the goal.…”

Section: Inadmissible Heuristicsmentioning

confidence: 99%

See 2 more Smart Citations

The Fifteen Puzzle—A New Approach through Hybridizing Three Heuristics Methods

Hasan¹,

Aladdin

Talabani³

et al. 2023

Computers

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The Fifteen Puzzle problem is one of the most classical problems that has captivated mathematics enthusiasts for centuries. This is mainly because of the huge size of the state space with approximately 1013 states that have to be explored, and several algorithms have been applied to solve the Fifteen Puzzle instances. In this paper, to manage this large state space, the bidirectional A* (BA*) search algorithm with three heuristics, such as Manhattan distance (MD), linear conflict (LC), and walking distance (WD), has been used to solve the Fifteen Puzzle problem. The three mentioned heuristics will be hybridized in a way that can dramatically reduce the number of states generated by the algorithm. Moreover, all these heuristics require only 25 KB of storage, but help the algorithm effectively reduce the number of generated states and expand fewer nodes. Our implementation of the BA* search can significantly reduce the space complexity, and guarantee either optimal or near-optimal solutions.

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Section: Inadmissible Heuristicsmentioning

confidence: 99%

Section: Inadmissible Heuristicsmentioning

confidence: 99%

Section: Inadmissible Heuristicsmentioning

confidence: 99%

See 1 more Smart Citation

The Fifteen Puzzle—A New Approach through Hybridizing Three Heuristics Methods

Hasan¹,

Aladdin

Talabani³

et al. 2023

Computers

View full text Add to dashboard Cite

show abstract

“…As a result, the total number of food sources and the number of bees employed are equal. Another presumption is that the number of bees working and the number of bees watching are equal [33][34][35].…”

Section: Artificial Bee Colony (Abc)mentioning

confidence: 99%

Optimization of fractional order PI controller using meta-heuristics algorithms applied to multilevel inverter for grid-connected PV

Wafa,

Raihane,

Hani

2023

Diagnostyka

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Due to its multiple advantages in industrial and grid-connected applications, Multi-Level Inverters (MLIs) have increased in popularity in recent years. To improve the efficiency of a grid-connected PV system's integrated multi-level inverter fractional order PI (FOPI) controllers are used to describe the control process. The control system is made up of three control loops based on FOPI controllers: one for controlling the intermediate circuit voltage (Vdc) and the other two for controlling the direct and quadratic currents (Id, Iq) supplied by the multilevel inverter. The proposed controller parameters (K p , K I , λ)must be selected in order to increase the efficiency of the multi-level inverter while decreasing the total harmonic distortion (THD) of the output current of the inverter as well as voltage. For this we used three meta-heuristic algorithms (PSO, ABC, GWO). The performance of the three controllers PSO-FOPI, ABC-FOPI and GWO-FOPI controller is compared. The findings showed that GWO-FOPI performs better than the other PSO-FOPI and ABC-FOPI in accuracy and total harmonic distortion THD term. The simulation will be conducted using Matlab/Simulink.

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“…R Yao et al found that the hysteresis model is complex and non-differentiable, which leads to the complexity of gradient acquisition, and to solve this problem, the authors proposed an improved ABC and used it for the identification of lag parameters, and finally verified the feasibility of the method in the identification of nonlinear hysteresis parameters, although this method improves the identification performance of nonlinear hysteresis parameters, it does not consider the identification problem of other linear parameters [11]. A Tuncer found that the traditional algorithm, can only provide small-scale solutions for the N-puzzle problem, to achieve the solution of the 15-puzzle problem, the authors proposed a new algorithm built on the metaheuristic algorithm, which divides the puzzle, and uses ABC to solve the divided the results show that the method helps significantly in solving the 15-puzzle problem, this method only divides the problem, simplifies the solving steps, but has little effect on the solving calculation of the problem [12].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation Model of Corporate Financial Sustainability based on Swarm Algorithm

Chang

2024

SCPE

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In traditional financial performance evaluation models, parameter settings are often too large or too small, resulting in significant model errors. To address this issue, an improved artificial bee colony algorithm was proposed and applied to optimize the parameters of performance evaluation models. This method first constructs a corporate financial performance evaluation system, and then improves the artificial bee colony algorithm with differential evolution algorithm to optimize the parameters of the long short-term memory network, in order to improve the accuracy of the long short-term memory network in corporate financial performance evaluation. The results showed that the improvement of the ABC algorithm was effective. The improved ABC algorithm converged on the Ackley function in the 800th iteration, and the ABC algorithm converged in the 1400th iteration. The evaluation error of the proposed method is the lowest, with the algorithm having the lowest four errors of -0.0121, 0.0453, 0.0683, and 0.0047, respectively. Among the other algorithms, the comprehensive error of the financial performance evaluation model based on Long Short Term Memory (LSTM) network is relatively low, but still lower than the algorithm proposed in the study. The research proposes a long short-term memory network optimized based on improved artificial bee colony algorithm, which can accurately evaluate the financial performance of enterprises, help them review their own development level, and clarify their future development direction.

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15-Puzzle Problem Solving with the Artificial Bee Colony Algorithm Based on Pattern Database

Cited by 5 publications

References 14 publications

The Fifteen Puzzle—A New Approach through Hybridizing Three Heuristics Methods

The Fifteen Puzzle—A New Approach through Hybridizing Three Heuristics Methods

Optimization of fractional order PI controller using meta-heuristics algorithms applied to multilevel inverter for grid-connected PV

Performance Evaluation Model of Corporate Financial Sustainability based on Swarm Algorithm

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