linear programming

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Words related to linear programming

a mathematical technique used in economics

References in periodicals archive ?
After getting the predicted importance score for each sentence in the given paper, we exploit the integer linear programming method to generate well-structured slides by selecting and aligning key phrases and sentences.
Shakeri and Logendran (2007) studied the problem of production scheduling model as a mixed integer linear programming (binary) developed for scheduling tasks in multitasking environments, for which the number of completed tasks was not a good measure.
Consider the following fuzzy integer linear programming (P), with trapezoidal fuzzy variables.
In this document, we proposed a mixed integer linear programming model for the optimal assignation of the work shift applied to a real case of physiotherapists in the intensive and intermediate care area in a clinic.
3 O'Hara's algorithm as an integer linear programming problem
These methods utilized biased sampling and integer linear programming (ILP) in two phases for the tour scheduling of a PT workforce.
The integer linear programming formulation of the model is shown in Appendix 1.
Sarper [14] modelled the two-machine flow shop scheduling problem as a mixed integer linear programming formulation and suggested three constructive heuristics.
They present a methodology for achieving optimal deadlock prevention by converting a variety of problems under consideration into integer linear programming models.
Samani and Mottaghi [26] used the integer linear programming for obtaining the optimum pipe sizes and reservoir elevations in pipe networks.
They advance to multi-objective problems, including interactive multiple criteria decision-making approaches, integer linear programming, networks, dynamic programming, modeling techniques, heuristics, nonlinear programming and discrete-event simulation, with a foray into inventory management.
Most significant, the new release delivers Mixed Integer Linear Programming (MILP) - which is critically acclaimed in the optimization community.
Several methods such as mixed integer linear programming [2], mixed integer nonlinear programming [3], dynamic programming [4] and methods involving simulated annealing [5], genetic algorithm (GA) [6], particle swarm optimization (PSO) [7], ant colony optimization [8], invasive weed optimization [9] and biogeography based optimization [10] have been suggested for solving DG placement problems.
Support for integer linear programming, choice of solver methods, automatic plotting of objective function and constraints in the Optimization Assistant.