Search Results - (( optimal ((search algorithm) OR (graph algorithm)) ) OR ( optical code algorithm ))
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Synthesis of transistor-chaining algorithm for CMOS cell layout using bipartite graph / Azizi Misnan
Published 1997“…A depth - first search algorithm is used to search for optimal chaining. …”
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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
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African Buffalo Optimization (ABO): A New Metaheuristic Algorithm
Published 2015“…This paper proposes a new meta-heuristic approach to solving numerical and graph-based problems. The African buffalo algorithm evolved from an understanding of the animal's survival instincts and the search techniques they utilize in the African forests and savannahs; the search for the optimal path to pasture is aligned to their cooperative, intelligent, and social nature. …”
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VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…Visualization techniques help in understanding the searching behaviour of Genetic Algorithm. lt also makes possible the user interactions during the searching process. …”
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Enhancing three variants of harmony search algorithm for continuous optimization problems
Published 2021“…Meta-heuristic algorithms are well-known optimization methods, for solving real-world optimization problems. …”
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A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network
Published 2018“…The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. …”
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Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system
Published 2021“…This solution depending on applying the optimization on an optimal path while the traditional ACO is optimizing the random path based on the greedy algorithm hence we get the most optimal path. …”
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A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network
Published 2015“…The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. …”
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Combinatorial test suites generation strategy utilizing the whale optimization algorithm
Published 2020“…In the last 15 years, applications of meta-heuristics as the backbone of t-way test suite generation have shown promising results (e.g. Particle Swarm Optimization, Cuckoo Search, Flower Pollination Algorithm, and Hyper-Heuristics (HHH), to name a few). …”
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Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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Test case minimization applying firefly algorithm
Published 2018“…The proposed test case minimization method has the following steps: provide weight to the paths, calculate path coverage for each path, transform an immediate graph into an adjacency matrix, which later is used to apply firefly algorithm and generate optimal test cases. …”
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Novel Adaptive Bacterial Foraging Algorithms for Global Optimisation with Application to Modelling of a TRS
Published 2015“…The constant step size in the original bacterial foraging algorithm causes oscillation in the convergence graph where bacteria are not able to reach the optimum location with large step size, hence reducing the accuracy of the final solution. …”
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A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem
Published 2009“…The OCGA is compared with other well known local search method namely dynamic length tabu search, randomised steepest descent method, and other variants of genetic algorithms using extensive data sets collected from the literatures. …”
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Modification of particle swarm optimization algorithm for optimization of discrete values
Published 2011“…Stochastic optimization algorithms are a new breed of optimizers that have recently been developed. …”
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Sequence t-way test generation using the barnacles mating optimizer algorithm
Published 2021“…More precisely, we focus on the generation of test cases due to the ordering of inputs (or sequence) using the newly developed Barnacles Mating Optimizer (BMO) Algorithm. Our experience with BSS is encouraging as we manage to match some of existing best test suite size for small interaction strength (t<5) with small number of event sequences (≤10). …”
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A branch and bound and simulated annealing approach for job shop scheduling
Published 2004“…In the branch and bound approach, the job shop scheduling problem is represented by a disjunctive graph, then the optimal schedule is obtained using the branch and bound algorithm while simulated annealing is a local search based algorithm which will slightly perturb the initial feasible solution to decrease the makespan. …”
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Recent research in cooperative path planning algorithms for multi-agent using mixed- integer linear programming
Published 2016“…This paper will review and compare the performances of those existing methods that can find solution without graph search algorithm such as Mixed-Integer Linear Programming (MILP) techniques which exactly solves the problem and then propose four alternative MILP formulations which are computationally less intensive and suited for real-time purposes, but yield a theoretically guaranteed suboptimal solution.…”
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Automated Examination Timetabling System (AETSys) / Ariff Md Ab Malik
Published 2013“…This system has been developed based on a hybridization of local search-population based metaheuristic algorithms. …”
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Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem
Published 2017“…This process is a crucial task because it can affect the convergence speed and also the quality of the final solution (Rahnamayan, Tizhoosh, & Salama, 2007).This study able to produce a set of initial solution, therefore it is able to contribute to the improvement phase of approach that uses population of initial solutions such as ant colony optimization (ACO) (Socha, Joshua, & Michael, 2002), genetic algorithm (GA) (Lewis & Paechter, 2005), and harmony search algorithm (HSA) (Al-Betar & Khader, 2010).The approach in this study also shows that a feasible timetable can be found for numerous data set problems.…”
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