Sentence examples for linear programming procedure from inspiring English sources

The first is a sequential mixed integer linear programming procedure that iteratively refines the discretization of the maneuvers to yield a trade-off between computational time and cost.

First, an MILP (mixed integer linear programming) procedure is used to solve the water and energy allocation problem regarding several objectives.

These two algorithms are different: the GIMME is a linear programming procedure, while the iMAT is a mixed integer linear programming procedure.

In this paper we describes the cost efficiency of Dutch hospitals using the method of Data Envelopment Analysis DEAa), a linear programming procedure for determining a frontier or best practice of resource usage and service delivery.

More recent advances include OptForce, which maximizes product yield by knockout, inhibition, and activation targets, relative to a wild-type flux distribution [ 14], and EMILiO, which rapidly identifies the optimal set of modified reactions and their optimal fluxes using a successive linear programming procedure [ 11].

For instance, Golany (1988) first presented a MODEA model which is designed as an interactive multi-objective linear programming (MOLP) procedure to select the preferred output targets given the input levels.

In this paper we show how each of these seemingly different problems can be formulated as a sequential (set) partitioning problem, and solved using a parametric linear programming (LP) procedure.

Based on the concept of gene interaction, Antonov et al (2004) proposed a Maximal Margin Linear Programming (MAMA) procedure that combines linear programming (LP) and SVM [ 16].

Their algorithm consists of two procedures, namely linear programming and sequential heuristic procedures that fulfill the major and remaining portions of the item demands, respectively.

To overcome this difficulty, this paper presents two mixed integer linear programming (MILP -based procedures to generate a few structurally different starting points for the NLP.

Wang and Elhag (2006) developed a non-linear programming solution procedure using a fuzzy TOPSIS method based on a cut level concept.