scholarly journals Metode Simulated Annealing untuk Optimasi Penjadwalan Perkuliahan Perguruan Tinggi

2016 ◽  
Vol 6 (2) ◽  
pp. 133
Author(s):  
Wiktasari Sari ◽  
Jatmiko Endro Suseno
Keyword(s):  
Simulated Annealing ◽  
Time Slot ◽  
Heuristic Method ◽  
Optimal Solution ◽  
Search Space ◽  
Course Scheduling ◽  
Time Period ◽  
Method Of Solution ◽  
Class Room ◽  
Annealing Method

Course scheduling an assignment of courses and lecturers in the available time slots involving certain restrictions. Simulated annealing is a heuristic method can be used as search method and provide acceptable solutions with good results. The research aims to make scheduling courses at the college using simulated annealing using five variables data that lecturer courses, the time slot is comprised of the day and the time period and class room. The research has two objective functions to be generated, the first is the assignment of a lecturer on courses that will be of teaching, second lecturers and their assignment course on the time slot and the room available. The objective function is calculated by taking into account the restrictions involved to produce the optimal solution. The validation is performed by testing to simulated annealing method with an varian average of 77.791% of the data variance can reach a solution with a standard deviation of 3.931509. In this research given the method of solution in the use of the remaining search space to be reused by the data that is unallocated.

scholarly journals BOOSTING SIMULATED ANNEALING WITH FITNESS LANDSCAPE PARAMETERS FOR BETTER OPTIMALITY

2015 ◽  
pp. 107-112
Author(s):  
Sunanda Gupta ◽  
Sakshi Arora
Keyword(s):  
Simulated Annealing ◽  
Probability Function ◽  
Fitness Landscape ◽  
Optimal Solution ◽  
Search Space ◽  
Solution Quality ◽  
Acceptance Probability ◽  
Evaluation Strategies ◽  
Fitness Distance Correlation ◽  
The Cost

Multi Dimensional Knapsack problem is a widely studied NP hard problem requiring extensive processing to achieve optimality. Simulated Annealing (SA) unlike other is capable of providing fast solutions but at the cost of solution quality. This paper focuses on making SA robust in terms of solution quality while assuring faster convergence by incorporating effective fitness landscape parameters. For this it proposes to modify the ‘Acceptance Probability’ function of SA. The fitness landscape evaluation strategies are embedded to Acceptance Probability Function to identify the exploitation and exploration of the search space and analyze the behavior on the performance of SA. The basis of doing so is that SA in the process of reaching optimality ignores the association between the search space and fitness space and focuses only on the comparison of current solution with optimal solution on the basis of temperature settings at that point. The idea is implemented in two different ways i.e. by making use of Fitness Distance Correlation and Auto Correlation functions. The experiments are conducted to evaluate the resulting SA on the range of MKP instances available in the OR library.

Whale optimization algorithm based on lateral inhibition for image matching and vision-guided AUV docking

2020 ◽  
pp. 1-12
Author(s):  
Zheping Yan ◽  
Jinzhong Zhang ◽  
Jialing Tang
Keyword(s):  
Lateral Inhibition ◽  
Optimization Algorithm ◽  
Image Matching ◽  
Autonomous Underwater Vehicle ◽  
Optimal Solution ◽  
Search Space ◽  
Whale Optimization Algorithm ◽  
Inhibition Mechanism ◽  
Whale Optimization ◽  
Accuracy And Stability

The accuracy and stability of relative pose estimation of an autonomous underwater vehicle (AUV) and a target depend on whether the characteristics of the underwater image can be accurately and quickly extracted. In this paper, a whale optimization algorithm (WOA) based on lateral inhibition (LI) is proposed to solve the image matching and vision-guided AUV docking problem. The proposed method is named the LI-WOA. The WOA is motivated by the behavior of humpback whales, and it mainly imitates encircling prey, bubble-net attacking and searching for prey to obtain the globally optimal solution in the search space. The WOA not only balances exploration and exploitation but also has a faster convergence speed, higher calculation accuracy and stronger robustness than other approaches. The lateral inhibition mechanism can effectively perform image enhancement and image edge extraction to improve the accuracy and stability of image matching. The LI-WOA combines the optimization efficiency of the WOA and the matching accuracy of the LI mechanism to improve convergence accuracy and the correct matching rate. To verify its effectiveness and feasibility, the WOA is compared with other algorithms by maximizing the similarity between the original image and the template image. The experimental results show that the LI-WOA has a better average value, a higher correct rate, less execution time and stronger robustness than other algorithms. The LI-WOA is an effective and stable method for solving the image matching and vision-guided AUV docking problem.

A simulation study of self-assembly of ABC star terpolymers confined between two parallel surfaces

Soft Matter ◽  
2021 ◽  
Author(s):  
Zhiyao Liu ◽  
Zheng Wang ◽  
Yuhua Yin ◽  
Run Jiang ◽  
Baohui Li
Keyword(s):  
Simulated Annealing ◽  
Phase Behavior ◽  
Phase Diagrams ◽  
Simulation Study ◽  
Self Assembly ◽  
Simulated Annealing Method ◽  
Parallel Surfaces ◽  
Annealing Method

Phase behavior of ABC star terpolymers confined between two identical parallel surfaces is systematically studied with a simulated annealing method. Several phase diagrams are constructed for systems with different bulk...

scholarly journals Optimum Distribution System Expansion Planning Incorporating DG Based on N-1 Criterion for Sustainable System

2021 ◽  
Vol 13 (12) ◽  
pp. 6708
Author(s):  
Hamza Mubarak ◽  
Nurulafiqah Nadzirah Mansor ◽  
Hazlie Mokhlis ◽  
Mahazani Mohamad ◽  
Hasmaini Mohamad ◽  
...  
Keyword(s):  
Power Systems ◽  
Distribution System ◽  
Industrial Revolution ◽  
Optimal Solution ◽  
Search Space ◽  
Planning Problem ◽  
System Expansion ◽  
Optimum Distribution ◽  
Optimal Sizing ◽  
Expansion Planning

Demand for continuous and reliable power supply has significantly increased, especially in this Industrial Revolution 4.0 era. In this regard, adequate planning of electrical power systems considering persistent load growth, increased integration of distributed generators (DGs), optimal system operation during N-1 contingencies, and compliance to the existing system constraints are paramount. However, these issues need to be parallelly addressed for optimum distribution system planning. Consequently, the planning optimization problem would become more complex due to the various technical and operational constraints as well as the enormous search space. To address these considerations, this paper proposes a strategy to obtain one optimal solution for the distribution system expansion planning by considering N-1 system contingencies for all branches and DG optimal sizing and placement as well as fluctuations in the load profiles. In this work, a hybrid firefly algorithm and particle swarm optimization (FA-PSO) was proposed to determine the optimal solution for the expansion planning problem. The validity of the proposed method was tested on IEEE 33- and 69-bus systems. The results show that incorporating DGs with optimal sizing and location minimizes the investment and power loss cost for the 33-bus system by 42.18% and 14.63%, respectively, and for the 69-system by 31.53% and 12%, respectively. In addition, comparative studies were done with a different model from the literature to verify the robustness of the proposed method.

scholarly journals Benchmarking Quantum Annealing Against “Hard” Instances of the Bipartite Matching Problem

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Daniel Vert ◽  
Renaud Sirdey ◽  
Stéphane Louise
Keyword(s):  
Simulated Annealing ◽  
Polynomial Time ◽  
Optimal Solution ◽  
Quantum Computers ◽  
Quantum Annealing ◽  
Maximum Cardinality ◽  
Matching Problem ◽  
Bipartite Matching ◽  
Wave Device ◽  
D Wave

AbstractThis paper experimentally investigates the behavior of analog quantum computers as commercialized by D-Wave when confronted to instances of the maximum cardinality matching problem which is specifically designed to be hard to solve by means of simulated annealing. We benchmark a D-Wave “Washington” (2X) with 1098 operational qubits on various sizes of such instances and observe that for all but the most trivially small of these it fails to obtain an optimal solution. Thus, our results suggest that quantum annealing, at least as implemented in a D-Wave device, falls in the same pitfalls as simulated annealing and hence provides additional evidences suggesting that there exist polynomial-time problems that such a machine cannot solve efficiently to optimality. Additionally, we investigate the extent to which the qubits interconnection topologies explains these latter experimental results. In particular, we provide evidences that the sparsity of these topologies which, as such, lead to QUBO problems of artificially inflated sizes can partly explain the aforementioned disappointing observations. Therefore, this paper hints that denser interconnection topologies are necessary to unleash the potential of the quantum annealing approach.

Locally optimal solution of robust ex-core detector response using constrained simulated annealing

2009 ◽  
Vol 239 (1) ◽  
pp. 51-57 ◽  
Author(s):  
Ho-Cheol Shin ◽  
Moon-Ghu Park ◽  
Sung-Tae Yang ◽  
Kyung-Ho Roh ◽  
Sang-Rae Moon ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Optimal Solution ◽  
Detector Response ◽  
Constrained Simulated Annealing ◽  
Locally Optimal Solution

Component Rearrangement on Printed Wiring Boards to Maximize the Fundamental Natural Frequency

1993 ◽  
Vol 115 (3) ◽  
pp. 312-321 ◽  
Author(s):  
Tien-Sheng Chang ◽  
E. B. Magrab
Keyword(s):  
Simulated Annealing ◽  
Boundary Conditions ◽  
Natural Frequency ◽  
Printed Wiring Board ◽  
Computationally Efficient ◽  
Additional Increase ◽  
Simulated Annealing Method ◽  
Fundamental Natural Frequency ◽  
Rearrangement Algorithm ◽  
Annealing Method

A methodology to attain the highest fundamental natural frequency of a printed wiring board by rearranging its components has been developed. A general two-dimensional rearrangement algorithm is developed by which the rearrangement of the component-lead-board (CLB) assemblies is performed automatically for any combination of equal size, unequal size, movable and immovable CLBs. This algorithm is also capable of incorporating two design restrictions: fixed (immovable) components and prohibited (non-swappable) areas. A highly computationally efficient objective function for the evaluation of the automatic rearrangement process is introduced, which is a linear function of the size of the individual CLBs that have been selected for each interchange. The simulated annealing method is adapted to solve the combinatorial rearrangement of the CLBs. Using 61 combinations of boundary conditions, equal and unequal sized CLBs, movable and immovable CLBs, various CLB groupings and sets of material properties, it is found that, when compared to the exact solution obtained by an exhaustive search method, the simulated annealing method obtained the highest fundamental natural frequency within 1 percent for 87 percent of the cases considered, within 0.5 percent for 72 percent of the cases and the true maximum in 43 percent of them. To further increase the fundamental natural frequency the introduction of a single interior point support is analyzed. Depending on the boundary conditions an additional increase in the maximum fundamental natural frequency of 44 to 198 percent can be obtained.

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