scholarly journals Penerapan Metode Steepest Ascent Hill Climb pada Permainan Puzzle

2018 ◽  
Vol 3 (2) ◽  
pp. 36
Author(s):  
Hairul Anam ◽  
Feby Sabilhul Hanafi ◽  
Ahmad Fauzal Adifia ◽  
Ahmad Firdaus Ababil ◽  
Saiful Bukhori
Keyword(s):  
Artificial Intelligence ◽  
Optimization Problems ◽  
Search Algorithms ◽  
Hill Climbing ◽  
Optimal Time ◽  
Hill Climbing Algorithm ◽  
Steepest Ascent ◽  
The Hill

Puzzle is one example of the application of artificial intelligence, in the process of completion there are many search algorithms that can be applied. The 8 puzzle solution will be faster obtained if the array principle is used with a variation of the Steepest-Ascent Hill Climbing (Hill Climbing algorithm by choosing the sharpest / steepest slope) with the correct heuristic parameters and distance heuristics and combined with LogList as the storage state ever passed to overcome the problems in the hill climbing algorithm itself and avoid the looping state that has been passed. Steepest Ascent Hill Climbing is an algorithm method that is widely used for optimization problems. The application of the SAHC (Steepest Ascent Hill Climbing) Algorithm to the puzzle is needed so that the game is completed with optimal time.

scholarly journals IMPLEMENTASI ALGORITMA HILL CLIMBING PADA PENENTUAN JARAK TERPENDEK KOTA WISATA DI INDONESIA

2019 ◽  
Vol 1 (3) ◽  
pp. 127-132
Author(s):  
Desti Fitriati ◽  
Nura Meutia Nessrayasa
Keyword(s):  
Optimization Problems ◽  
Complex Problem ◽  
Hill Climbing ◽  
Hill Climbing Algorithm ◽  
Steepest Ascent ◽  
Shortest Route ◽  
Shortest Distance ◽  
Optimization Function ◽  
The Right

Searching and determining the shortest route is a complex problem, looking for the shortest route from a number of attractions and the distance between attractions. With varying access paths, the shortest route search becomes the right choice using a website-based app that provides the closest route on a map using the SAHC (Steepest Ascent Hill Climbing) algorithm. Steepest Ascent Hill Climbing is a method of an algorithm that is widely used for optimization problems. One application is to find the shortest route by maximizing or minimizing the value of the existing optimization function. In research ii study using 34 provinces in Indonesia and every province, there are 5 most popular tour, accuracy value obtained in research determination of the shortest distance of tourist city in Indonesia is 93,3%.  

scholarly journals Rancang Bangun Aplikasi Puzzle Tokoh Walisongo Metode Steepest Ascent Hill Climbing Berbasis Android

2020 ◽  
Vol 1 (1) ◽  
pp. 15-19
Author(s):  
Khairil Anam ◽  
Eko Duwi Prastiyo
Keyword(s):  
Optimization Problems ◽  
Hill Climbing ◽  
Steepest Ascent

Game is one of the applications that can improve one's development and thinkingpower. When someone plays the game, it is indirectly required to complete the missionand obstacles in the game. That is why playing games can be said to enhance one'sdevelopment and thinking power. One game that can improve the development of one'sthinking power is a puzzle game. Puzzle is a game that is played in pairs and pairs, soas to produce something that has been determined by a system. This puzzle game isvery popular with children, adolescents, adults and also parents. Stepest Ascent HillClimbing searches based on the best heuristic value. In this case the use of the operatordoes not determine the inventor of the solution. Steepest Ascent Hill Climbing is analgorithm method that is widely used for optimization problems

The Optimization Method to Transfer Bus Routes for Rail Transit Terminal Station

2012 ◽  
Vol 253-255 ◽  
pp. 1869-1875
Author(s):  
Sheng Zhang ◽  
Wu Sheng Liu
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Optimization Method ◽  
Hill Climbing ◽  
Rail Transit ◽  
Hill Climbing Algorithm ◽  
Variation Rate ◽  
Encoding Method ◽  
The Hill ◽  
Terminal Station

The optimization model is framed with a goal to minimize overall consumption of travel time for passengers. A variety of constrains are considered, including time, capacity, stop number, profit and so on. According to the features of the model, the hill-climbing algorithm is adopted to obtain the initial solution, which reduces the time of optimization. Meanwhile, direct order encoding method, namely node method, is introduced for encoding, construct a Hybrid Genetic Algorithm for the solution. The results show that adapter value is more steady and the model result is preferable when the variation rate is increased while the number of iteration is decreased.

scholarly journals Optimal Identification and Metaheuristic PID Control of a Two-Tank System

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1101
Author(s):  
Dan Stefanoiu ◽  
Janetta Culita
Keyword(s):  
Process Model ◽  
Robustness Analysis ◽  
Hill Climbing ◽  
Tuning Parameters ◽  
Hill Climbing Algorithm ◽  
Optimal Controllers ◽  
Tank System ◽  
Bounded Error ◽  
The Hill ◽  
Modern Optimization

In the modern optimization context, this paper introduces an optimal PID-based control strategy for a two-tank installation, namely ASTANK2. The process model was identified by using raw and spline smoothed measured data, respectively. Two PID controller configurations, a standard (regular) one (PID-R) and a non-standard one (PID-N), were considered for each type of model, resulting in four regulators. The optimal tuning parameters of each regulator were obtained by a searching approach relying on a combination of two metaheuristics. Firstly, an improved version of the Hill Climbing algorithm was employed to comprehensively explore the searching space, aiming to find fairly accurate tuning parameters. Secondly, an improved version of the Firefly Algorithm was proposed to intensively refine the search around the previously found optimal parameters. A comparative analysis between the four controllers was achieved in terms of performance and robustness. The simulation results showed that all optimal controllers yielded good performance in the presence of exogenous stochastic noise (bounded error tracking, setpoint tracking, reduced overshoot, short settling time). Robustness analysis is extensive and illustrates that the PID-R controllers are more robust to model uncertainties, whilst PID-N controllers are more robust to tracking staircase type references.

Smooth gait optimization of a fish robot using the genetic-hill climbing algorithm

Robotica ◽  
2011 ◽  
Vol 30 (2) ◽  
pp. 257-278 ◽  
Author(s):  
Tuong Quan Vo ◽  
Hyoung Seok Kim ◽  
Byung Ryong Lee
Keyword(s):  
Genetic Algorithm ◽  
Hill Climbing ◽  
Optimal Parameters ◽  
Fish Robot ◽  
Hill Climbing Algorithm ◽  
Smooth Motion ◽  
Simulation Results ◽  
The Hill ◽  
Gait Optimization ◽  
Input Torque

SUMMARYThis paper presents a model of a three-joint (four links) carangiform fish robot. The smooth gait or smooth motion of a fish robot is optimized by using a combination of the Genetic Algorithm (GA) and the Hill Climbing Algorithm (HCA) with respect to its dynamic system. Genetic algorithm is used to create an initial set of optimal parameters for the two input torque functions of the system. This set is then optimized by using HCA to ensure that the final set of optimal parameters is a “near” global optimization result. Finally, the simulation results are presented in order to demonstrate that the proposed method is effective.

Low Side Lobe On-chip Two Dimensional Optical Phased Array Based on the Hill Climbing Algorithm

2018 ◽  
Vol 47 (9) ◽  
pp. 913001
Author(s):  
杜书剑 DU Shu-jian ◽  
章羚璇 ZHANG Ling-xuan ◽  
王国玺 WANG Guo-xi ◽  
李中宇 LI Zhong-yu ◽  
张其浩 ZHANG Qi-hao ◽  
...  
Keyword(s):  
Phased Array ◽  
Side Lobe ◽  
Hill Climbing ◽  
Two Dimensional ◽  
Hill Climbing Algorithm ◽  
Optical Phased Array ◽  
On Chip ◽  
The Hill
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