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heuristic search algorithm
This paper presents a family of sub-optimal algorithms based on the A* heuristic search algorithm, aimed at solving the general job-shop scheduling problem.
      
Based on this model, a heuristic search algorithm is developed for finding a near-optimal ordering of negotiation issues and their parameters.
      
The Guided Genetic Algorithm (GCA) is a hybrid of Genetic Algorithm and Guided Local Search, a meta-heuristic search algorithm.
      
The genetic algorithm (GA) is known to be a modern heuristic search algorithm, and is suitable for solving such a problem.
      
We develop an approach for implementing a real time admissible heuristic search algorithm for solving project scheduling problems with resource constraints.
      
A system-wide multi-commodity integer network flow model and a heuristic search algorithm for the above purpose are presented and discussed in this paper.
      
This paper explores the use of the meta-heuristic search algorithm Simulated Annealing for solving a minimum cost network synthesis problem.
      
To find the best model, we use a heuristic search algorithm in which the structure is determined incrementally.
      
An efficient heuristic search algorithm is important in extracting the pathway from the observation.
      
Genetic Algorithms are adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic.
      
However, any heuristic search algorithm chosen for this purpose may introduce a bias favoring some of the criteria.
      
Heuristic search algorithm using simulated annealing or genetic algorithms have been implemented.
      
It is an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetics.
      
Maximum parsimony analyses were conducted using the heuristic search algorithm with 1,000 random additions.
      
Parsimony analyses were conducted using the heuristic search algorithm with 500 random input orders and tree bisection-reconnection branch swapping.
      
The method we used for weighted graph coloring is based on simulated annealing, which is a heuristic search algorithm.
      
The nucleotide phylogenetic tree was constructed using the heuristic search algorithm.
      
 

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