For over four decades, Introduction to Operations Research has been the classic text on operations research. While building on the classic strengths of the text, the author continues to find new ways to make the text current and relevant to students. One way is by incorporating a wealth of state-of-the-art, user-friendly software and more coverage of business applications than ever before. The hallmark features of this edition include new section and chapters, updated problems, clear and comprehensive coverage of fundamentals, an extensive set of interesting problems and cases, and state-of-the-practice operations research software used in conjunction with examples from the text.
McGraw-Hill's Connect, is also available as an optional, add on item. Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need, when they need it, how they need it, so that class time is more effective. Connect allows the professor to assign homework, quizzes, and tests easily and automatically grades and records the scores of the student's work. Problems are randomized to prevent sharing of answers an may also have a "multi-step solution" which helps move the students' learning along if they experience difficulty.
Professor emeritus of operations research at Stanford University. Dr. Hillier is especially known for his classic, award-winning text, Introduction to Operations Research, co-authored with the late Gerald J. Lieberman, which has been translated into well over a dozen languages and is currently in its 8th edition. The 6th edition won honorable mention for the 1995 Lanchester Prize (best English-language publication of any kind in the field) and Dr. Hillier also was awarded the 2004 INFORMS Expository Writing Award for the 8th edition. His other books include The Evaluation of Risky Interrelated Investments, Queueing Tables and Graphs, Introduction to Stochastic Models in Operations Research, and Introduction to Mathematical Programming. He received his BS in industrial engineering and doctorate specializing in operations research and management science from Stanford University. The winner of many awards in high school and college for writing, mathematics, debate, and music, he ranked first in his undergraduate engineering class and was awarded three national fellowships (National Science Foundation, Tau Beta Pi, and Danforth) for graduate study. Dr. Hillier’s research has extended into a variety of areas, including integer programming, queueing theory and its application, statistical quality control, and production and operations management. He also has won a major prize for research in capital budgeting.
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从教学法和可读性的角度来看,这本书的文字风格非常学术化,几乎没有使用任何幽默或比喻来缓解阅读的枯燥感。这使得它非常适合作为研究生或高年级本科生的主教材,因为这类读者已经习惯了这种直接、精确的表达方式。然而,对于自学者或者对数学有天然畏惧感的读者来说,可能会觉得阅读过程像是在啃一块硬骨头,需要极强的毅力和高度的专注力。书中图表的运用相对克制,大多是流程图或矩阵表示,清晰但缺乏视觉上的吸引力。总而言之,这是一部严肃的、内容密度极高的学术著作,它的目标是教会你如何精确思考和建模,而不是让你轻松愉快地度过阅读时光。如果你追求的是深度和严谨性,那么这本书绝对是值得投入时间的,但请做好准备,这不是一本能让你捧着咖啡惬意阅读的休闲读物。
评分这本书的封面设计得相当朴素,那种传统的学术书籍风格,硬壳封面,颜色是深沉的蓝色,配上白色的字体,非常中规中矩。我拿到手的时候,感觉它很有分量,一看就知道是那种需要认真对待的教材。翻开扉页,首先映入眼帘的是密密麻麻的作者介绍和前言,看得出编者在内容组织上是下了大功夫的,但坦白说,对于初学者来说,这些文字堆砌在一起,确实有点让人望而生畏。我当时的心情是既期待又有点紧张,毕竟“运筹学”这个名字听起来就带着一股严肃的数学气息。装帧质量摸上去很扎实,感觉能抗住几年图书馆的周转和我的反复翻阅,这一点我很满意,毕竟好书经得起折腾。内页的纸张略微偏黄,这对于长时间阅读来说是个加分项,能减轻眼睛的疲劳。整体而言,这本书的物理呈现给人一种可靠、严谨的学术工具书的印象,没有花哨的设计,一切都以内容为中心,这对于一本理工科教材来说,或许是最好的定位。
评分这本书的习题设置是其最核心的价值之一,也是我用来检验学习效果的主要手段。习题的难度梯度设置得非常合理,从基础的计算题到需要综合运用多个章节知识的证明题,覆盖面很广。我发现,很多理论上看起来很清楚的概念,只有在尝试自己解决那些稍微复杂一点的习题时,才会暴露出自己理解上的漏洞。书中提供的答案和详细步骤(虽然我买的版本没有提供完整的解答手册,但对部分关键习题的解析很到位),是自我学习中至关重要的反馈机制。我花了大量时间在那些关于对偶性和敏感性分析的习题上,每次解开一个复杂的对偶问题,都会有一种豁然开朗的感觉,这无疑极大地增强了我对运筹学这门学科的信心。可以说,这本书的价值,很大一部分体现在这些精心设计的练习题中。
评分内容深度方面,这本书显然是面向有一定基础的读者的。我刚开始接触这些概念时,很多定义和定理的推导过程读起来是相当晦涩的。它没有像一些入门读物那样,用大量生活中的例子来“软化”复杂的数学模型,而是直接将核心理论摆在面前,期望读者能自行消化吸收其中的逻辑。比如,线性规划的单纯形法,它的每一步迭代和变量切换的原理,书中阐述得非常细致,但对于第一次接触的读者来说,可能需要配合大量的练习和辅助资料才能真正理解其背后的数学直觉。书中的章节结构安排得非常逻辑化,从基础的线性代数回顾到网络流、动态规划,层层递进,体现了编者对学科脉络的深刻把握。不过,这种严谨性也带来了一个挑战,那就是阅读节奏相对缓慢,我常常需要停下来,在草稿纸上演算半天,才能确保自己跟上了作者的思路,这对于追求快速掌握核心技能的读者来说,可能会感到一丝受挫。
评分我特别注意到书中在案例分析部分的处理方式。它似乎更倾向于展示经典、教科书式的应用场景,比如资源分配、生产计划优化这类问题。这些案例的设置非常清晰,目标函数和约束条件的建立过程清晰可见,是学习如何将实际问题转化为数学模型的好范本。但是,我个人感觉,如果能加入一些更贴近现代工业或服务业的、稍微复杂一些的、带有不确定性的实际问题分析,可能会让这本书的实用价值更上一层楼。当前的案例虽然严谨,但略显“理想化”。例如,在讨论整数规划时,虽然理论讲解透彻,但缺乏一个关于如何在实际大规模数据集中快速找到可行解的启发性讨论。总而言之,它是一本打地基的绝佳教材,但对于想要马上“盖楼”的工程师来说,可能还需要额外的实战经验来补充。
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