Handbook of Approximation Algorithms and Metaheuristics, Second Edition: Two-Volume Set
暫譯: 近似演算法與元啟發式方法手冊（第二版）：雙卷套裝

Teofilo F. Gonzalez

Handbook of Approximation Algorithms and Metaheuristics, Second Edition: Two-Volume Set
  • 出版商: CRC
  • 出版日期: 2020-09-30
  • 售價: $3,970
  • 貴賓價: 9.5 折 $3,772
  • 語言: 英文
  • 頁數: 1578
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 0367570289
  • ISBN-13: 9780367570286
  • 相關分類: Algorithms-data-structures

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics.

Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems.

 

Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more.

商品描述(中文翻譯)

《近似演算法與元啟發式方法手冊（第二版）》反映了過去二十年該領域的巨大成長。透過來自領先專家的貢獻，本手冊提供了對基礎理論和方法論的全面介紹，以及近似演算法和元啟發式方法的各種應用。

這套兩卷本的第一卷主要處理方法論和傳統應用。它包括限制、放鬆、局部比率、近似方案、隨機化、禁忌搜尋、演化計算、局部搜尋、神經網絡及其他元啟發式方法。它還探討了多目標優化、重新優化、敏感度分析和穩定性。涵蓋的傳統應用包括：箱子打包、多維打包、斯坦納樹、旅行推銷員、排程及相關問題。

第二卷專注於方法論在組合優化、計算幾何和圖形問題中的當代及新興應用，以及在大規模和新興應用領域中的應用。它包括用於聚類、網絡（感測器和無線）、通信、生物信息學搜尋、流媒體、虛擬社區等的近似演算法和啟發式方法。

作者簡介

About the Editor

Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of scheduling, graph, computational geometry, communication, routing, etc.

Teofilo Gonzalez is a professor of computer science at the University of California, Santa Barbara.

作者簡介(中文翻譯)

編輯介紹

Teofilo F. Gonzalez是加州大學聖塔巴巴拉分校的計算機科學名譽教授。他於1975年在明尼蘇達大學獲得博士學位。在加入UCSB計算機科學系之前，他曾在奧克拉荷馬大學、賓夕法尼亞州立大學和德克薩斯州達拉斯大學任教。他曾在蒙特雷科技與高等教育學院和烏特勒支大學進行學術休假。他以在近似問題的困難性方面的開創性研究而聞名，該研究被廣泛引用；他為k-tMM聚類提出的次線性和最佳近似算法；他引入了開放式車間排程問題及其解決算法，這些算法在許多研究領域中得到了應用；以及他在排程、圖形、計算幾何、通信、路由等領域問題的研究。

Teofilo Gonzalez是加州大學聖塔巴巴拉分校的計算機科學教授。

類似商品