Sentence examples for multiple objectives using from inspiring English sources

Both the pre-treatment and trans-esterification sections of this process are simulated in a process simulator followed by optimization for multiple objectives using multi-objective differential evolution with taboo list.

Sandwich panels are optimized for multiple, conflicting objectives using an integer-coded non-dominated sorting genetic algorithm.

Genetic Algorithm (GA) methodology was used in the multiple objective optimization (using MATLAB R2010a software) to find the optimum cutting conditions for defect free drilling.

The genetic algorithm that is effective in accomplishing multiple objectives is used to optimize the fuzzy model predictive controller.

A control system design procedure based on the optmllsation of mUltiple objectives is used to address the control design requirements of a simulated gasification plant.

More generally, in the event that multiple objectives are used within a MOO procedure, each function's relative importance could be weighted by adjusting the optimization parameters, such as weights θk (Equation 4).

Objectives used included 5× and 10× magnification.

This is one of the first works in using multiple objectives in the design of supply chain networks.

It solves very large problems with very high numbers of constraints under multiple objective conditions by using advanced optimization services that is implemented through genetic algorithms and evolutionary programming.

To demonstrate how these methods work, the well-known redundancy allocation problem was solved as a multiple objective problem by using the NSGA genetic algorithm to initially find the Pareto optimal solutions, and then, the two proposed methods are applied to prune the Pareto set.

Finally, the proposed multi-objective genetic algorithm (MOGA) based system uses the generalized Parato-based scale independent fitness function (GPSIFF) as the fitness function to evaluate the multiple objectives for chromosomes and used to find the Pareto-optimal kanban number and size for multiple objectives, i.e., maximizing mean throughput rate and minimizing mean total WIP inventory.