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A local search algorithm has been developed for problem solution for large-scale networks.
Quite recently some efficient methods with relaxed proximal matrix [21 24] have been developed for Problem (1).
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The conventional tools of decision-making in water resources infrastructure planning have been developed for problems with well-characterized uncertainties and are ill-suited for problems involving climate nonstationarity.
Due to the computational intractability, two recently developed solution methods, based on swarm intelligence technique, are developed for problem solution, namely, particle swarm optimization (PSO) and bacterial colony optimization (BCO).
A local search algorithm is developed for problem solution.
In this paper, new complex maps are developed for problems containing a single near-boundary critical point.
A deterministic timed colored Petri net model has been developed for scheduling problem.
Many heuristics have been developed for this problem, as well as optimal solution methods which are applicable only to small instances.
Arguably the most successful set of computational tools for ncRNA exploration have been developed for the problem of ncRNA validation.
Several methods have been developed for this problem.
Although a number of algorithms and tools have been developed for this problem (e.g. Andronescu et al., 2007; Do et al., 2006a; Hamada et al., 2008; Hofacker et al., 1994; Parisien and Major, 2008), their accuracies are limited.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com