I strongly recommend it to anyone interested in linear programming. The book covers major theoretical developments of the the last ten years as well as practical issues related to implementation of the methods. The subject is presented thoroughly, and valuable insight and motivation are also provided. The book can be used as an introduction to interior-point methods for advanced students and is a useful reference book for researchers. I am sure I am going to use the book a lot and cite it often.
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This book presents the major primal-dual algorithms for linear programming in straightforward terms. A thorough description of the theoretical properties of these methods is given, as are a discussion of practical and computational aspects and a summary of current software. This is an excellent, timely, and well-written work. A unified treatment of superlinear convergence, finite termination, and detection of infeasible problems is presented. Issues relevant to practical implementation are also discussed, including sparse linear algebra and a complete specification of Mehrotra's predictor-corrector algorithm.