scholarly journals A Hybridalldifferent-Tabu Search Algorithm for Solving Sudoku Puzzles

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Ricardo Soto ◽  
Broderick Crawford ◽  
Cristian Galleguillos ◽  
Fernando Paredes ◽  
Enrique Norero
Keyword(s):  
Tabu Search ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Search Procedure ◽  
Global Constraint ◽  
Approximate Methods ◽  
Complete Collection ◽  
Robust Approach ◽  
Np Complete ◽  
Exact And Approximate Methods

The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. It consists in filling an2 × n2grid, composed ofncolumns,nrows, andnsubgrids, each one containing distinct integers from 1 ton2. Such a puzzle belongs to the NP-complete collection of problems, to which there exist diverse exact and approximate methods able to solve it. In this paper, we propose a new hybrid algorithm that smartly combines a classic tabu search procedure with thealldifferentglobal constraint from the constraint programming world. Thealldifferentconstraint is known to be efficient for domain filtering in the presence of constraints that must be pairwise different, which are exactly the kind of constraints that Sudokus own. This ability clearly alleviates the work of the tabu search, resulting in a faster and more robust approach for solving Sudokus. We illustrate interesting experimental results where our proposed algorithm outperforms the best results previously reported by hybrids and approximate methods.

scholarly journals GASAT: A Genetic Local Search Algorithm for the Satisfiability Problem

2006 ◽  
Vol 14 (2) ◽  
pp. 223-253 ◽  
Author(s):  
Frédéric Lardeux ◽  
Frédéric Saubion ◽  
Jin-Kao Hao
Keyword(s):  
Tabu Search ◽  
Local Search ◽  
Hybrid Algorithm ◽  
State Of The Art ◽  
Search Algorithm ◽  
Satisfiability Problem ◽  
Local Search Algorithm ◽  
Overall Performance ◽  
Genetic Local Search ◽  
Search Stage

This paper presents GASAT, a hybrid algorithm for the satisfiability problem (SAT). The main feature of GASAT is that it includes a recombination stage based on a specific crossover and a tabu search stage. We have conducted experiments to evaluate the different components of GASAT and to compare its overall performance with state-of-the-art SAT algorithms. These experiments show that GASAT provides very competitive results.

A Filter-and-Fan Metaheuristic for the 0-1 Multidimensional Knapsack Problem

2012 ◽  
Vol 3 (4) ◽  
pp. 43-63 ◽  
Author(s):  
Mahdi Khemakhem ◽  
Boukthir Haddar ◽  
Khalil Chebil ◽  
Saïd Hanafi
Keyword(s):  
Tabu Search ◽  
Knapsack Problem ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Benchmark Problems ◽  
Tree Search ◽  
Search Procedure ◽  
Multidimensional Knapsack Problem ◽  
Multidimensional Knapsack ◽  
Adaptive Neighborhood

This paper proposes a new hybrid tree search algorithm to the Multidimensional Knapsack Problem (MKP) that effectively combines tabu search with a dynamic and adaptive neighborhood search procedure. The authors’ heuristic, based on a filter-and-fan (F&F) procedure, uses a Linear Programming-based Heuristic to generate a starting solution to the F&F process. A tabu search procedure is used to try to enhance the best solution value provided by the F&F method that generates compound moves by a strategically truncated form of tree search. They report the first application of the F&F method to the MKP. Experimental results obtained on a wide set of benchmark problems clearly demonstrate the competitiveness of the proposed method compared to the state-of-the-art heuristic methods.

Hybrid Particle Swarm: Tabu Search Optimization Algorithm for Parameter Estimation

2013 ◽  
Author(s):  
Anish Sebastian ◽  
Marco P. Schoen
Keyword(s):  
Tabu Search ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Single Agent ◽  
Particle Swarm ◽  
Estimation Problem ◽  
Benchmark Problems ◽  
Force Output ◽  
Semg Signal ◽  
Advantages And Disadvantages

A hybrid intelligent algorithm is proposed. The algorithm utilizes a particle swarm and a Tabu search algorithm. Swarm based algorithms and single agent based algorithms each, have distinct advantages and disadvantages. The goal of the presented work is to combine the strengths of the two different algorithms in order to achieve a more effective optimization routine. The developed hybrid algorithm is tailored such that it has the capability to adapt to the given cost function during the optimization process. The proposed algorithm is tested on a set of different benchmark problems. In addition, the hybrid algorithm is utilized for solving the estimation problem encountered for estimating the finger force output given a surface electromyogram (sEMG) signal at the input. This estimation problem is commonly encountered while developing a control system for a prosthetic hand.

scholarly journals Newly Elaborated Hybrid Algorithm for Optimization of Robot Arm’s Trajectory in Order to Increase Efficiency and Provide Sustainability in Production

2021 ◽  
Vol 13 (15) ◽  
pp. 8193
Author(s):  
Rabab Benotsmane ◽  
László Dudás ◽  
György Kovács
Keyword(s):  
Tabu Search ◽  
Cycle Time ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Raw Materials ◽  
Industrial Robots ◽  
Motion Path ◽  
Environmental Damage ◽  
Robot Arm ◽  
Manufacturing Companies

Nowadays, resources for production (raw materials, human, energy, etc.) are limited, while population, consumption and environmental damage are continuously increasing. Consequently, the current practices of resource usage are not sustainable. Therefore, manufacturing companies have to change to environmentally friendly and innovative technologies and tools, e.g., industrial robots. Robots are necessary in the production sector and also in terms of sustainability: (1) the application of robots is needed to compensate for the lack of human resources; (2) robots can increase productivity significantly; and (3) there are several hazardous (e.g., chemical, physical) industrial tasks for which robots are more adequate than human workforce. This article introduces a newly elaborated Hybrid Algorithm for optimization of a robot arm’s trajectory by the selection of that trajectory that has the smallest cycle time. This Hybrid Algorithm is based on the Tabu Search Algorithm and also uses two added methods—Point Insertion and Grid Refinement—simultaneously to find more precisely the optimal motion path of the robot arm in order to further reduce the cycle time and utilize the joints’ torque more efficiently. This Hybrid Algorithm is even more effective than applying the Tabu Search method alone and results in even higher efficiency improvement. The Hybrid Algorithm is executed using MATLAB software by creating a dynamic model of a 5 degree-of-freedom robot arm. The main contribution of the research is the elaboration of the new Hybrid Algorithm, which results in the minimization of robot arms’ motion cycle times, causing a significant increase in productivity and thus a reduction in specific production cost; furthermore, obstacles in the workspace can be avoided. The efficiency of the Hybrid Algorithm is validated by a case study showing that application of the new algorithm resulted in 32% shorter motion cycle time.

scholarly journals An enhanced Tabu search Cell formation Algorithm for Cellular Manufacturing System

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Tabu Search ◽  
Hybrid Algorithm ◽  
Manufacturing Systems ◽  
Cellular Manufacturing ◽  
Search Algorithm ◽  
Cell Formation ◽  
Primary Objective ◽  
Intracellular Movement ◽  
Multiple Routes ◽  
Machine Cell

The major benefit of using Cellular manufacturing systems (CMS) is the improvement in efficiency and reduction in the production time. In a CMS the part families and machine parts are identified to minimise the inter and intracellular movement and maximise the utilisation of machines within each cell. Many scholars have proposed methods for the evaluation of machine cell part layouts with single routes; this paper introduces a modified Hybrid Tabu Search Algorithm (HTSA) referred to as Hybrid Algorithm in this study for machine cell part layouts having multiple routes as well. The primary objective of this paper is to minimise the inter and intracellular movement using a hybrid algorithm. The paper presents a comparative analysis of the existing and the proposed algorithms, proving that the proposed hybrid algorithm is simple, easy to understand, and has a remarkable efficiency with a runtime of 5.6 seconds.

scholarly journals Hybrid genetic–tabu search algorithm to optimize the route for capacitated vehicle routing problem with time window

2020 ◽  
Vol 1 (1) ◽  
pp. 15 ◽  
Author(s):  
Mohammad Deni Akbar ◽  
Rio Aurachmana
Keyword(s):  
Tabu Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Optimum Number ◽  
Tabu Search Algorithm ◽  
Routing Problem ◽  
Capacitated Vehicle Routing Problem ◽  
Capacitated Vehicle

Optimization of transportation and distribution costs is one of the important issues in the supply chain management area. It is caused by their large contribution to the logistics costs that can reach up to 40%. Thus, choosing the right route is one of the efforts that can be done to resolve the issue. This study aims to optimize the capacitated vehicle routing problem with time windows (CVRPTW) for mineral water company distributor with pick-up and delivery problem. To achieve the aim, this study used hybrid algorithm, Genetic Algorithm (GA) and Tabu Search Algorithm (TS). The selection of this hybrid algorithm is due to its capability in minimizing travel distance. The result of this study shows that not only the algorithm has successfully reduced the existing route but also predicted the optimum number of homogenous fleet. By running the algorithm, this study concludes that the number of the optimum routes for this study can be reduced for up to 15.99% than the existing route.

scholarly journals DTW-Global Constraint Learning Using Tabu Search Algorithm

2016 ◽  
Vol 82 ◽  
pp. 12-19 ◽  
Author(s):  
Bilel Ben Ali ◽  
Youssef Masmoudi ◽  
Souhail Dhouib
Keyword(s):  
Tabu Search ◽  
Search Algorithm ◽  
Tabu Search Algorithm ◽  
Global Constraint ◽  
Constraint Learning

A hybrid algorithm Tabu Search – GRASP for wounded evacuation in disaster response

2020 ◽  
Vol 54 (1) ◽  
pp. 19-36
Author(s):  
Mohamad Khorbatly ◽  
Hamdi Dkhil ◽  
Hassan Alabboud ◽  
Adnan Yassine
Keyword(s):  
Tabu Search ◽  
Disaster Response ◽  
Hybrid Algorithm ◽  
Complex Problem ◽  
Informed Decision Making ◽  
Search Procedure ◽  
Adaptive Search ◽  
Resource Assignment ◽  
Negative Effects ◽  
Evacuation Plan

Natural and triggered-disasters, have devastating and profound negative effects on human lives that require a speedy declaration of an emergency in order to minimize their severe consequences. Hence, a prompt disaster response, in addition to effective measures such as informed decision making, organized evacuation plan, right hospital selection, proper rescue vehicles, efficient resources assignment and timely vehicle scheduling are critical actions needed to organize successful secured operations that could, if well prepared, save many injured bodies and lessen the human distress. To reach this ultimate goal, a complicated procedure should be in place and any failure can potentially increase the number of causalities, thus a complete alertness and full caution should be exercised. In this paper, we treat the Integrated Problem of Ambulance Scheduling and Resource Assignment (IPASRA) in the case of a sudden disaster. The main resources to be assigned are the ambulances and the hospitals. While, the hospitals serving capacities might be considered or not according to the extent of disaster and particularly to the wounded bodies’ total number. We formulate the (IPASRA) as a linear model, furthermore a novel hybrid algorithm based on Tabu Search (TS) and Greedy Randomized Adaptive Search Procedure (GRASP) is offered to tackle this complex problem. Simulation tests are also presented to prove the efficiency of our modelling and resolution approaches.

scholarly journals Hybridizing Beam Search with Tabu Search for the Irregular Packing Problem

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yunqing Rao ◽  
Peng Wang ◽  
Qiang Luo
Keyword(s):  
Tabu Search ◽  
Hybrid Algorithm ◽  
Numerical Experiments ◽  
Search Algorithm ◽  
Packing Problem ◽  
Benchmark Problems ◽  
Beam Search ◽  
Hybrid Search

The irregular packing problem involves arranging all the irregular pieces on a plate with the objective of maximizing the use of material. In this article, the layout is formed by the ordered sequence of the irregular pieces which is obtained by a hybrid search algorithm and where the order is decoded by a proposed placement principle. First, a novel no-fit-polygon (NFP) generator is introduced. Then, a placement principle is presented with the new NFP generator. Finally, a search algorithm hybridized with beam search (BS) and tabu search (TS) is proposed to search over the sequence. The numerical experiments with many benchmark problems show that the hybrid algorithm is an applicative and effective approach for solving the irregular packing problem. The hybrid algorithm can produce competitive solutions in less time than many other typical algorithms.

scholarly journals An application and Parallel Tabu Search Algorithm for Solving the PTSP Under the OpenMP-MPI Environment

2020 ◽  
Author(s):  
Mohamed Abdellahi Amar ◽  
Walid Khaznaji
Keyword(s):  
Tabu Search ◽  
Traveling Salesman Problem ◽  
Search Algorithm ◽  
A Priori ◽  
Traveling Salesman ◽  
Deterministic Models ◽  
Expected Length ◽  
Np Complete ◽  
Parallel Tabu Search ◽  
Real World Problems

<div>This paper reviews some real-world problems modeling</div><div>as Probabilistic Traveling Salesman Problem (PTSP), by</div><div>presenting the important results found in the literature. It</div><div>illustrates the usefulness of the inclusion of probabilistic elements in deterministic models. We propose a new modeling of the PTSP by the deviations of the routing of a robot in order to avoid obstacles which are not foreseen in its path. The Probabilistic Traveling Salesman Problem(PTSP) is a variation of the classic Traveling Salesman Problem (TSP) where each node i is present</div><div>with probability pi. The solution for the PTSP consists in finding an a priori tour that visits all the cities that minimizes the expected length of the tour. From the litterateur the PTSP is NP-Complete, therefore the execution time is a prime factor in its resolution. In the last of his paper we present a new parallel Tabu search heuristic for solving PTSP by using the Open MPI environment.</div>

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