Optimum Synthesis of Mechanisms Using Tabu-Gradient Search Algorithm

2004 ◽  
Vol 127 (5) ◽  
pp. 917-923 ◽  
Author(s):  
Ahmad A. Smaili ◽  
Nadim A. Diab ◽  
Naji A. Atallah
Keyword(s):  
Tabu Search ◽  
Short Term Memory ◽  
Search Algorithm ◽  
Gradient Algorithm ◽  
Gradient Search ◽  
Planar Mechanisms ◽  
Optimum Synthesis ◽  
Synthesis Of Mechanisms ◽  
Tabu Search Method ◽  
Optimization Schemes

A tabu-gradient search is herein presented for optimum synthesis of planar mechanisms. The solution generated by a recency-based, short term memory tabu search is used to start a gradient search to drive the solution ever closer to the global minimum. A brief overview of the tabu-search method is first presented. A tabu-gradient algorithm is then used to synthesize four-bar mechanisms for path generation tasks by way of three examples, including two benchmark examples used before to test other deterministic and intelligent optimization schemes. Compared with the corresponding results generated by other schemes, the tabu-gradient search rendered the most optimal solutions of all.

A Tabu-Gradient Search-Based Optimization Technique for Synthesis of Mechanisms

2004 ◽  
Author(s):  
Ahmad Smaili ◽  
Naji Atallah
Keyword(s):  
Tabu Search ◽  
Global Minimum ◽  
Short Term Memory ◽  
Search Algorithm ◽  
Random Search ◽  
Optimization Technique ◽  
Optimization Methods ◽  
Gradient Search ◽  
Optimum Synthesis ◽  
Timing Task

Mechanism synthesis requires the use of optimization methods to obtain approximate solution whenever the desired number of positions the mechanism is required to traverse exceeds a few (five in a 4R linkage). Deterministic gradient-based methods are usually impractical when used alone because they move in the direction of local minima. Random search methods on the other hand have a better chance of converging to a global minimum. This paper presents a tabu-gradient search based method for optimum synthesis of planar mechanisms. Using recency-based short-term memory strategy, tabu-search is initially used to find a solution near global minimum, followed by a gradient search to move the solution ever closer to the global minimum. A brief review of tabu search method is presented. Then, tabu-gradient search algorithm is applied to synthesize a four-bar mechanism for a 10-point path generation with prescribed timing task. As expected, Tabu-gradient base search resulted in a better solution with less number of iterations and shorter run-time.

Optimum Synthesis of Rigid Mechanisms Using Real Coded Quantum-Inspired Evolution Algorithm (RQIEA) With Neighborhood Search

2007 ◽  
Author(s):  
Ahmad Smaili ◽  
Mazen Hassanieh ◽  
Bachir Chaaya ◽  
Fawzan Al Fares
Keyword(s):  
Quantum Computing ◽  
Search Algorithm ◽  
Random Search ◽  
Quantum Gates ◽  
Neighborhood Search ◽  
Gradient Search ◽  
Quantum Bits ◽  
Optimum Synthesis ◽  
Evolution Algorithm ◽  
Optimization Schemes

A modified real coded quantum-inspired evolution algorithm (MRQIEA) is herein presented for optimum synthesis of planar rigid body mechanisms (RBMs). The MRQIEA employs elements of quantum computing such as quantum bits, registers, and quantum gates, neighborhood search engine, and gradient search to form a random search algorithm for solution optimization of a wide class of problems. A brief overview of the quantum computing elements and their adaptation to the optimization algorithm is first presented. The algorithm is then adapted to the synthesis problem of RBMs. Finally, the algorithm is demonstrated and compared to other search methods by way of three examples, including two benchmark examples that have been used in the literature to assess the performance of other optimization schemes.

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.

Optimum Synthesis of Rigid Mechanisms Using a Dynamic Ant-Search Method With Sensitivity Analysis

2019 ◽  
Author(s):  
Nadim Diab ◽  
Omar Itani ◽  
Ahmad Smaili
Keyword(s):  
Sensitivity Analysis ◽  
Optimization Technique ◽  
Design Parameters ◽  
Neighborhood Search ◽  
Intensity Level ◽  
Path Generation ◽  
Exploration And Exploitation ◽  
Planar Mechanisms ◽  
Optimum Synthesis ◽  
Synthesis Of Mechanisms

Abstract Four-bar linkages are commonly used mechanisms in various mechanical systems and components. Several techniques for optimum synthesis of planar mechanisms have been suggested in literature such as the Genetic, Tabu, Simulated Annealing, Swarm-Based and many other algorithms. This paper covers optimization of four-bar mechanisms with path generation tasks using a Dynamic Ant Search (DAS) algorithm. Unlike the Modified Ant Search (MAS) technique where ants unanimously moved between the exploration and exploitation phases, in the proposed algorithm, each ant is free to travel between the two aforementioned phases independent of other ants and as governed by its own pheromone intensity level. Moreover, sensitivity analysis is conducted on the design parameters to determine their corresponding neighborhood search boundaries and thus improve the search while in the exploitation mode. These implemented changes demonstrated a remarkable impact on the optimum synthesis of mechanisms for path generation tasks. A briefing of the MAS based algorithm is first presented after which the proposed modified optimization technique and its implementation on four-bar mechanisms are furnished. Finally, three case studies are conducted to evaluate the efficiency and robustness of the proposed methodology where the performances of the obtained optimum designs are benchmarked with those previously reported in literature.

A New Approach for Exact/Approximate Point Synthesis of Planar Mechanisms

2005 ◽  
Author(s):  
Ahmad Smaili ◽  
Nadim Diab
Keyword(s):  
Synthesis Method ◽  
Dimensional Synthesis ◽  
Gradient Search ◽  
Planar Mechanisms ◽  
Simple Method ◽  
New Approach ◽  
Optimum Synthesis ◽  
Approximate Synthesis ◽  
Optimum Solution ◽  
Synthesis Approach

The aim of this article is to provide a simple method to solve the mixed exact-approximate dimensional synthesis problem of planar mechanism. The method results in a mechanism that can traverse a closed path with the choice of any number of exact points while the rest are approximate points. The algorithm is based on optimum synthesis rather than on precision position methods. Ant-gradient search is applied on an objective function based on log10 of the error between the desired positions and those generated by the optimum solution. The log10 function discriminates on the side of generating miniscule errors (on the order of 10−14) at the exact points while allowing for higher errors at the approximate positions. The algorithm is tested by way of five examples. One of these examples was used to test exact/approximate synthesis method based on precision point synthesis approach.

scholarly journals Design of Flotation Circuits Using Tabu-Search Algorithms: Multispecies, Equipment Design, and Profitability Parameters

Minerals ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 181 ◽  
Author(s):  
Freddy Lucay ◽  
Edelmira Gálvez ◽  
Luis Cisternas
Keyword(s):  
Tabu Search ◽  
Approximate Method ◽  
Short Term Memory ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Adaptive Procedure ◽  
Problem Size ◽  
Combinatorial Optimization Problems

The design of a flotation circuit based on optimization techniques requires a superstructure for representing a set of alternatives, a mathematical model for modeling the alternatives, and an optimization technique for solving the problem. The optimization techniques are classified into exact and approximate methods. The first has been widely used. However, the probability of finding an optimal solution decreases when the problem size increases. Genetic algorithms have been the approximate method used for designing flotation circuits when the studied problems were small. The Tabu-search algorithm (TSA) is an approximate method used for solving combinatorial optimization problems. This algorithm is an adaptive procedure that has the ability to employ many other methods. The TSA uses short-term memory to prevent the algorithm from being trapped in cycles. The TSA has many practical advantages but has not been used for designing flotation circuits. We propose using the TSA for solving the flotation circuit design problem. The TSA implemented in this work applies diversification and intensification strategies: diversification is used for exploring new regions, and intensification for exploring regions close to a good solution. Four cases were analyzed to demonstrate the applicability of the algorithm: different objective function, different mathematical models, and a benchmarking between TSA and Baron solver. The results indicate that the developed algorithm presents the ability to converge to a solution optimal or near optimal for a complex combination of requirements and constraints, whereas other methods do not. TSA and the Baron solver provide similar designs, but TSA is faster. We conclude that the developed TSA could be useful in the design of full-scale concentration circuits.

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.

Penentuan Rute Dan Penjadwalan Pengangkutan Sampah di Kota Bandung Wilayah Bandung Barat dengan Menggunakan Tabu Search

2020 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Yogi Yogaswara
Keyword(s):  
Tabu Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Initial Solution ◽  
Sequential Method ◽  
Routing Problem ◽  
Taboo Search ◽  
Total Distance ◽  
Tabu Search Method

Abstract― The route determination Model is commonly known as the Vehicle Routing Problem (VRP), VRP deals with determining the route to produce the best route in problems involving more than one vehicle with a certain capacity to serve a number of customer's point according to their respective demands, one of the main purpose of route determination is to minimize total distances. PD. Kebersihan Kota Bandung has been facing one of the problems related to vehicle routing since the route used for waste transport by the company currently does not pay attention to the location and distance of the TPS to be visited, resulting in a longer total distance of 564, 30 km. With the current routes, the company does not have a definite schedule of trash transport, this problem concern involve for trashbin heap. Therefore, VRP research was conducted to determine the transportation of waste routes in West Bandung area by producing solutions that can be proposed to reduce the total distances. The research was solved using the Tabu Search method, the application of this method requires the initial solution. In this study, the saving and sequential method insertion used to create the initial solution, then the initial solution was done repair by using the Tabu Search algorithm. The result of data processing with taboo Search generates 15 routes with the total mileage for each day of 448.48 km. Total distance generated by Tabu Search resulted in a decline of 115.82 km or give a savings of 20.53% from Total distance with the current route. Based on the route comes from Tabu Search, there is a schedule for garbage transport schedules in the TPS and obtained the total time of service by 15 vehicles on each day of 63.45 hours. Abstrak― Model penentuan rute pada umumnya dikenal dengan Vehicle Routing Problem (VRP), VRP berkaitan dengan penentuan rute untuk menghasilkan rute terbaik dalam permasalahan yang melibatkan lebih dari satu kendaraan dengan kapasitas tertentu untuk melayani sejumlah titik pelanggan sesuai dengan permintaan masing-masing, tujuan penentuan rute ini salah satunya adalah untuk meminimumkan jarak tempuh. Penentuan rute menjadi salah satu permasalahan PD. Kebersihan Kota Bandung yang bergerak dibidang pengangkutan sampah, karena rute yang digunakan oleh perusahaan saat ini tidak memperhatikan lokasi dan jarak Tempat Pembuangan Sementara (TPS) yang akan dikunjungi, sehingga menghasilkan total jarak tempuh yang lebih jauh yaitu sebesar 564,30 km. Dengan rute yang digunakan saat ini, perusahaan tidak memiliki jadwal pengangkutan sampah secara pasti yang memberikan kekhawatiran timbulnya penumpukan sampah. Oleh karena itu, dilakukan penelitian VRP untuk menentukan rute pengangkutan sampah diwilayah Bandung Barat dengan menghasilkan solusi yang dapat diajukan untuk mengurangi total jarak. Penelitian ini diselesaikan dengan menggunakan metode Tabu Search, penerapan metode ini memerlukan adanya solusi awal. Dalam penelitian ini, metode saving dan sequential insertion yang digunakan untuk membuat solusi awal, selanjutnya solusi awal tersebut dilakukan perbaikan dengan menggunakan algoritma Tabu Search. Hasil pengolahan data dengan Tabu Search menghasilkan 15 rute dengan total jarak tempuh untuk setiap harinya sebesar 448,48 km. Total jarak yang dihasilkan Tabu Search menghasilkan penurunan sebesar 115,82 km atau memberikan penghematan sebesar 20,53% dari total jarak dengan rute saat ini. Berdasarkan rute yang dihasilkan dari Tabu Search, selanjutnya dilakukan penjadwalan pengangkutan sampah disetiap TPS dan memperoleh waktu pelayanan yang dibutuhkan oleh 15 kendaraan setip harinya sebesar 63,45 jam.

scholarly journals An Improved Ant Colony Optimized Tabu Search Algorithm for Makespan Improvement in Job Shop

2019 ◽  
Vol 9 (2) ◽  
pp. 670-674
Keyword(s):  
Tabu Search ◽  
Completion Time ◽  
Job Shop ◽  
Short Term Memory ◽  
Search Algorithm ◽  
Ant Colony ◽  
Rollback Recovery ◽  
Short Term ◽  
Term Memory ◽  
Recovery Technique

In industries, the completion time of job problems is increased drastically in the production unit. In many existing kinds of research, the completion time i.e. makespan of the job is minimized using straight paths which is time-consuming. In this paper, we addressed this problem using an Improved Ant Colony Optimization and Tabu Search (ACOTS) algorithm by identifying the fault occurrence position exactly to rollback. Also, we used a short term memory-based rollback recovery technique to roll back to its own short term memory to reduce the completion time of the job. Short term memory is used to visit the recent movements in Tabu search. Our proposed ACOTS-Cmax approach is efficient and consumed less completion time compared to the ACO algorithm

scholarly journals Research of Bio-Inspired Geomagnetic Navigation for AUV Based on Evolutionary Gradient Search

2019 ◽  
Vol 37 (5) ◽  
pp. 865-870
Author(s):  
Jiaojiao Guo ◽  
Mingyong Liu ◽  
Kun Liu ◽  
Yun Niu ◽  
Mengfan Wang
Keyword(s):  
Search Strategy ◽  
Search Algorithm ◽  
Gradient Algorithm ◽  
Evolutionary Strategy ◽  
Evolutionary Search ◽  
Gradient Search ◽  
Simulation Results ◽  
Low Efficiency ◽  
Navigation Method ◽  
Function Extremum

At present, bio-inspired geomagnetic navigation is mostly based on evolutionary strategy, which requires long navigation time and low efficiency. To solve this problem, a bio-inspired geomagnetic navigation method for AUV based on evolutionary gradient search is proposed. Combining the bionic evolutionary search algorithm with the classical gradient algorithm to search the function extremum can not only ensure the global optimization of the search, but also have fast convergence, which can improve the efficiency of bio-inspired geomagnetic navigation. The simulation results show that this method does not need prior geomagnetic information and can complete navigation tasks according to the geomagnetic trend. Comparing with the evolutionary search strategy, the effectiveness and superiority of the evolutionary gradient search strategy are verified.

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