This attractive textbook with its easy-to-follow presentation provides a
down-to-earth introduction to operations research for students in a wide
range of fields such as engineering, business analytics, mathematics and
statistics, computer science, and econometrics. It is the result of many
years of teaching and collective feedback from students.The book covers
the basic models in both deterministic and stochastic operations
research and is a springboard to more specialized texts, either
practical or theoretical. The emphasis is on useful models and
interpreting the solutions in the context of concrete applications.The
text is divided into several parts. The first three chapters deal
exclusively with deterministic models, including linear programming with
sensitivity analysis, integer programming and heuristics, and network
analysis. The next three chapters primarily cover basic stochastic
models and techniques, including decision trees, dynamic programming,
optimal stopping, production planning, and inventory control. The final
five chapters contain more advanced material, such as discrete-time and
continuous-time Markov chains, Markov decision processes, queueing
models, and discrete-event simulation.Each chapter contains numerous
exercises, and a large selection of exercises includes solutions.
