The Basics of Practical Optimization
This textbook provides undergraduate students with an introduction to optimization and its uses for relevant and realistic problems. The only prerequisite for readers is a basic understanding of multivariable calculus because additional materials, such as explanations of matrix tools, are provided in a series of Asides both throughout the text at relevant points and in a handy appendix.
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answer the following barrier functions base point boundary branching method calculus class Chapter college-visit problem Complete the following Computational Problem concave consider constraint function constraint region convex corresponding current guess deﬁned deﬁniteness derivative dual linear program dynamic programming eigenvalues equation constraints exact line-search example Exercise Explain ﬁnal ﬁnd ﬁnding ﬁrst ﬁxed function f graph of f inequality constraints integer linear program integer-pairs inverse Lagrange multiplier Lagrangian Lagrangian function least remaining cost Lewiston maximize minimizing value model to answer Modeling Problem modiﬁcations monthly payment function multiplier rule 7.6 multistage decision process Newton’s optimization method node nonlinear objective function optimization model order of convergence pair penalized minimizers penalty function Portland positive-deﬁnite quadratic function quasi-Newton method satisﬁes scaling factor second-derivative matrix solve an optimization stage stationary point steepest descent steepest descent method step-factor subproblem Taylor quadratic term two-variable update vector-matrix-vector multiplication working-set method Write and solve xold zero