scholarly journals Shortest Distribution Route Determination Of Pesticides Product Using Tabu Search Algorithm (Case Study : CV. Buana Artha Mandiri, Sidoarjo, Indonesia)

2020 ◽  
Vol 1 (01) ◽  
pp. 56-60
Author(s):  
Yustina Ngatilah ◽  
Anasyah Septiara ◽  
Caecilia Pujiastuti ◽  
Desak Ayu Clara Dewanti
Keyword(s):  
Tabu Search ◽  
Search Algorithm ◽  
Distribution Area ◽  
Tabu Search Algorithm ◽  
Optimal Route ◽  
Industrial Chemicals ◽  
Large Area ◽  
Distribution Process ◽  
Tabu Search Method ◽  
Fixed Distribution

Distribution is activity of delivering goods or services from producers to consumers. CV. Artha BuanaMandiri is a company engaged in Agricultural Industrial Chemicals. The products produced by CV. Artha Buana Mandiri are pesticides. With a large area distribution, the company's distribution process is still considered to be less optimal because there is no fixed distribution route due to the large number of routes used for the East Java distribution area, causing delays in the distribution process of pesticide products. The purpose of this study is to minimize the distance to obtain the optimal distribution route. Optimal route determination is included in the problem of Traveling Salesman Problem (TSP). One solution to solve TSP problems is to use the Tabu Search Algorithm. Tabu Search is a metaheuristic method based on local search. The process of performance moves from one solution to the next by choosing the best solution. The main purpose of this method is to prevent the search process from re-searching the space of the solution that has been traced. From the calculation it can be seen that the optimal route of the Tabu Search method is better than the company route with an optimum route of 251.3 km.

Determination of the Multicast Optimal Route for Mobile Sinks in a Specified Deadline using Network Coding and Tabu Search Algorithm in Wireless Sensor Networks

2018 ◽  
Author(s):  
Ehsan Kharati ◽  
Mohamad Khalili ◽  
Hamid Kermajani
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Tabu Search ◽  
Network Coding ◽  
Search Algorithm ◽  
Wireless Sensor ◽  
Optimization Models ◽  
Tabu Search Algorithm ◽  
Optimal Route ◽  
Mobile Sinks

Recent studies have shown that the use of mobile sinks and Network Coding (NC) and determining the Sink Optimal Route (SOR) in wireless sensor networks (WSNs) reduces the energy consumption. The purpose of this paper is to determine the multicast SOR to move mobile sinks at specific deadline using NC and modeling and problem formulating based on a Mixed Integer Linear Programming (MILP) in WSNs. In this paper, we first show that finding the SOR is NP-hard, and then for determining the SOR, several convex optimization models are presented using Support Vector Regression (SVR). Solving these models in a polynomial time is not possible due to various parameters and limited resources of WSNs. To solve this problem in polynomial time, a Tabu Search algorithm is proposed to reduce runtime and energy consumption. Simulation results show that optimization models and proposed Tabu Search algorithm significantly reduce energy consumption and required time for computing than non-NC methods.

scholarly journals Parallel and Serial Graph Coloring Implementations with Tabu Search Method

2019 ◽  
Vol 8 (2) ◽  
pp. 1050-1056
Keyword(s):  
Tabu Search ◽  
Graph Coloring ◽  
Arbitrary Number ◽  
Search Algorithm ◽  
Search Method ◽  
Tabu Search Algorithm ◽  
Behavioral Performance ◽  
Parallel Implementations ◽  
Tabu Search Method

One of the well-known property of graph is graph coloring. Any two vertices of a graph are different colors such that they are adjacent to each other. The objective of this paper is to analyse the behavioral performance of Tabu Search method through serial and parallel implementations. We explore both parallel and serial Tabu search algorithm for graph coloring with arbitrary number of nodes.

scholarly journals A Tabu Search Algorithm for Fast Restoration of Large Area Breakdown in Distribution Systems

2010 ◽  
Vol 02 (01) ◽  
pp. 1-5 ◽  
Author(s):  
Jian LIU ◽  
Hongli CHENG ◽  
Xiaojun SHI ◽  
Jingqiu XU
Keyword(s):  
Tabu Search ◽  
Distribution Systems ◽  
Search Algorithm ◽  
Tabu Search Algorithm ◽  
Large Area

scholarly journals Penentuan Rute Terpendek Pendistribusian Tabung Gas Lpg 3 Kg Pt. Fega Gas Palu Pratama Menggunakan Algoritma Tabu Search

2020 ◽  
Vol 16 (2) ◽  
pp. 221-229
Author(s):  
Riswan ◽  
A Sahari ◽  
D Lusiyanti
Keyword(s):  
Tabu Search ◽  
Nearest Neighbor ◽  
Search Algorithm ◽  
Tabu Search Algorithm ◽  
Termination Criteria ◽  
Shortest Route ◽  
Tabu Search Method ◽  
Optimum Solution ◽  
Gas Cylinders

ABSTRACTDistribution is one of the important tools in the company business activities. The problem that is often occurred indistribution is the determination of the shortest route. The purpose of this study is optimitation distribution route of3 kg LPG gas cylinders which is carried out by PT. Fega Gas Palu Pratama in Palu City, considering that thiscompany has not used a particular method in determining the distribution route of 3 kg LPG gas cylinders. Themethod used in this study is the Tabu Search algorithm. The algorithm of the Tabu Search method are of follows,first by determine the initial solution using the closest Nearest Neighbor, determine alternatives by exchange 2points in the solution, evaluate alternative solutions, determine a new optimum solution, update the Tabu List, thenwhen the termination criteria are obtained then the Tabu Search algorithm will stop otherwise it will revert toexchanging 2 points evaluation. The process of calculating the Tabu Search algorithm is conducted manually andbuilt using MATLAB. Based on the research that has been done, it is obtained that the shortest, more efficient routeis 21.91 km which has reduction of 7.26 km from the initial route 29.17 km.Keywords : Algorithm Tabu Search, Distribution, Shortest Route.

scholarly journals Performance Improvement of Decision Tree: A Robust Classifier Using Tabu Search Algorithm

2021 ◽  
Vol 11 (15) ◽  
pp. 6728
Author(s):  
Muhammad Asfand Hafeez ◽  
Muhammad Rashid ◽  
Hassan Tariq ◽  
Zain Ul Abideen ◽  
Saud S. Alotaibi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Tabu Search ◽  
Decision Tree ◽  
Decision Trees ◽  
Search Algorithm ◽  
Learning Algorithms ◽  
Performance Comparison ◽  
Machine Learning Algorithms ◽  
Supervised Machine Learning ◽  
Tabu Search Algorithm

Classification and regression are the major applications of machine learning algorithms which are widely used to solve problems in numerous domains of engineering and computer science. Different classifiers based on the optimization of the decision tree have been proposed, however, it is still evolving over time. This paper presents a novel and robust classifier based on a decision tree and tabu search algorithms, respectively. In the aim of improving performance, our proposed algorithm constructs multiple decision trees while employing a tabu search algorithm to consistently monitor the leaf and decision nodes in the corresponding decision trees. Additionally, the used tabu search algorithm is responsible to balance the entropy of the corresponding decision trees. For training the model, we used the clinical data of COVID-19 patients to predict whether a patient is suffering. The experimental results were obtained using our proposed classifier based on the built-in sci-kit learn library in Python. The extensive analysis for the performance comparison was presented using Big O and statistical analysis for conventional supervised machine learning algorithms. Moreover, the performance comparison to optimized state-of-the-art classifiers is also presented. The achieved accuracy of 98%, the required execution time of 55.6 ms and the area under receiver operating characteristic (AUROC) for proposed method of 0.95 reveals that the proposed classifier algorithm is convenient for large datasets.

An extreme‐point tabu‐search algorithm for fixed‐charge network problems

Networks ◽  
2021 ◽  
Vol 77 (2) ◽  
pp. 322-340 ◽  
Author(s):  
Richard S. Barr ◽  
Fred Glover ◽  
Toby Huskinson ◽  
Gary Kochenberger
Keyword(s):  
Tabu Search ◽  
Extreme Point ◽  
Search Algorithm ◽  
Fixed Charge ◽  
Tabu Search Algorithm ◽  
Network Problems
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