Models, theory and computational methods for problems with discrete decision alternatives. Considers greedy algorithms, branch and bound, cutting plane methods, Lagrangian relaxation and heuristics. Models, algorithms, and theory of linear programming. LP geometry, primal, dual and revised simplex algorithms, duality theory, optimality conditions, sensitivity analyses, interior point methods, and computer implementations. Approaches include the use of intelligent heuristics, decomposition, lower bounding schemes, limited enumeration, and simple methods for quickly finding good feasible solutions.
Numerous examples taken from industry provide a foundation.
Explores techniques for problems involving more than one criterion that are measured on incommensurate scales, such as dollars, reliability, and quality of life. Topics include methods for generating nondominated solutions, interactive procedures for continuous problems, goal programming, multiattribute utility theory, and the analytic hierarchy process. Optimization of combinatorial structures. Stable marriages, shortest paths, maximum flows, minimum-cost flows, matching problems. Approximation algorithms for NP-hard problems.