# Operations research / Richard Bronson, Govindasami Naadimuthu

##### By: Bronson, Richard.

##### Contributor(s): Naadimuthu, Govindasami.

Material type: TextPublisher: New York: McGraw-Hill; 1997Edition: 2nd.Description: 456 p.ISBN: 9780070080201.Other title: Schaum's outline of operations research.Subject(s): Operations research | Operations research -- problems, exercises, etcDDC classification: 003Item type | Home library | Call number | Status | Date due | Barcode | Item holds |
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Book | KCST Library | 003 Br Op (Browse shelf) | Available | 1000001320 |

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002.09 Re Remarkable books : | 003 Br Op Operations research / | 003 Ch Sy Systems thinking, systems practice : | 003 Pr A practical introduction to hardware/software codesign / | 003 Sy SystemC and SystemC-AMS in practice : |

Chapter 1 MATHEMATICAL PROGRAMMING Optimization problems. Linear programs. Integer programs. Quadratic programs. Problem formulation. Solution convention.

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Chapter 2 LINEAR PROGRAMMING: BASIC CONCEPTS Nonnegativity conditions. Slack variables and surplus variables. Generating an initial feasible solution. Penalty costs. Standard form. Linear dependence and independence. Convex combinations. Convex sets. Extreme-point solutions. Basic feasible solutions.

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Chapter 3 LINEAR PROGRAMMING: THE SIMPLEX AND THE DUAL SIMPLEX METHODS The simplex tableau. A tableau simplification. The simplex method. Modifications for programs with artificial variables. The dual simplex method.

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Chapter 4 LINEAR PROGRAMMING: DUALITY AND SENSITIVITY ANALYSIS Symmetric duals. Dual solutions. Unsymmetric duals. Sensitivity analysis.

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Chapter 5 LINEAR PROGRAMMING: EXTENSIONS The revised simplex method. Karmarkar's algorithm. Summary of Karmarkar's iterative procedure. Transforming a linear programming problem into Karmarkar's special form.

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Chapter 6 INTEGER PROGRAMMING: BRANCH-AND-BOUND ALGORITHM First approximation. Branching. Bounding. Computational considerations.

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Chapter 7 INTEGER PROGRAMMING: CUT ALGORITHMS The Gomory algorithm. Computational considerations.

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Chapter 8 INTEGER PROGRAMMING: THE TRANSPORTATION ALGORITHM Standard form. The transportation algorithm. An initial basic solution. Test for optimality. Improving the solution. Degeneracy.

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Chapter 9 INTEGER PROGRAMMING: SCHEDULING MODELS Production problems. Transshipment problems. Assignment problems. The traveling salesperson problem.

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Chapter 10 NONLINEAR PROGRAMMING: SINGLE-VARIABLE OPTIMIZATION The problem. Local and global optima. Results from calculus. Sequential search techniques. Three-point interval search. Fibonacci search. Goldenmean search. Convex functions.

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Chapter 11 NONLINEAR PROGRAMMING: MULTIVARIABLE OPTIMIZATION WITHOUT CONSTRAINTS Local and global maxima. Gradient vector and Hessian matrix. Results from calculus. The method of steepest ascent. The Newton-Raphson method. The Fletcher-Powell method. Hooke-Jeeves' pattern search. A modified pattern search. Choice of an initial approximation. Concave functions.

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Chapter 12 NONLINEAR PROGRAMMING: MULTIVARIABLE OPTIMIZATION WITH CONSTRAINTS Standard forms. Lagrange multipliers. Newton-Raphson method. Penalty functions. Kuhn-Tucker conditions. Method of feasible directions.

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Chapter 13 NETWORK ANALYSIS Networks. Minimum-span problems. Shortest-route problems. Maximal-flow problems. Finding a positive-flow path.

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Chapter 14 PROJECT PLANNING USING PERT/CPM PERT/CPM. Construction of the network (arrow) diagram. Critical path computations for CPM. Critical path computations for PERT. Project time vs project cost.

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Chapter 15 INVENTORY MODELS Inventory. Fixed order quantity models. Fixed order period models. Single period models.

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Chapter 16 FORECASTING Forecasting. Regression methods. Simplex linear regression. Coefficients of correlation and determination. Standard error of estimate. Special case: logarithmic (exponential) models. Multiple regression. Smoothing methods. Moving averages. Weighted moving averages. Exponential smoothing. Exponential smoothing with trend (trend-adjusted exponential smoothing). Forecast accuracy. Forecasting time series with multiplicative model.

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Chapter 17 GAME THEORY Games. Strategies. Stable games. Unstable games. Solution by linear programming. Dominance.

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Chapter 18 DECISION THEORY Decision processes. Native decision criteria. A priori criterion. A posteriori criterion. Decision trees. Utility. Lotteries. Von Neumann utilities.

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Chapter 19 DYNAMIC PROGRAMMING Multistage decision processes. A mathematical program. Dynamic programming. Dynamic programming with discounting. Stochastic multistage decision processes. Policy tables.

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Chapter 20 FINITE MARKOV CHAINS Markov processes. Powers of stochastic matrices. Ergodic matrices. Regular matrices.

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Chapter 21 MARKOVIAN BIRTH-DEATH PROCESSES Population growth processes. Generalized Markovian birth-death processes. Linear Markovian birth processes. Linear Markovian death processes. Linear Markovian birth-death processes. Poisson birth processos. Poisson death processes. Poisson birth-death processes.

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Chapter 22 QUEUEING SYSTEMS Introduction. Queue characteristics. Arrival patterns. Service patterns. System capacity. Queue disciplines. Kendall's notation.

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Chapter 23 M/M/1 SYSTEMS System characteristics. The Markovian model. Steady-state solutions. Measures of effectiveness.

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Chapter 24 OTHER SYSTEMS WITH POISSON-TYPE INPUT AND EXPONENTIAL-TYPE SERVICE TIMES State-dependent processes. Little's formulas. Balking and reneging. M/M/s systems. M/M/1/K systems. M/M/s/K systems.

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ANSWERS TO SUPPLEMENTARY PROBLEMS 422 (31)

INDEX 453

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