Многокритериальная оптимизация. Теория, вычисления и приложения: Theory, Computation, and Application
A text on operations research statistics designed for junior and senior graduate courses in multiple criteria decision making, multiple criteria optimization, and multiple objective programming. Shows how to implement the techniques of multiple criteria optimization for solving large-scale multiple objective problems on a computer. Contains full details on such recent breakthrough developments as the Tchebycheff method, a method that enables one to solve large-scale multiple objective linear, integer and nonlinear programming problems. Includes numerous exercises for solving problems manually and by using a computer.
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SINGLE OBJECTIVE LINEAR PROGRAMMING
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ADBASE algorithm augmented weighted Tchebycheff basis coefficients column compute Consider the MOLP constraints contour convex combination convex cone criterion cone criterion value decision maker domination set efficient extreme points efficient points efficient set elements feasible region Figure forward filtering go to Step Goal Programming Graph of Example interactive interval criterion weights Job class level curves lexicographic linear fractional program linearly independent LP max max Objs minimal MOLFP MPSX multiple objective linear multiple objective program nondominated criterion vectors nonlinear nonnegative null vector objective function objective function gradients objective function value objective linear programming obtain Operational Research optimal bases optimal extreme points optimal point optimal solution optimal tableau parametric diagram parametrically optimal Phase pivot problem procedure relative interior Section seed point simplex method Specify Steuer subproblem test subset Theorem unbounded edge utility function vector-maximum w-efficient weighted Tchebycheff program weighted-sums LP weighting vector X-vectors