By Dorit Hochbaum
Approximation set of rules for scheduling / Leslie A. corridor -- Approximation algorithms for bin packing : a survey / E.G. Coffmann, Jr., M.R. Garey, and D.S. Johnson -- Approximating overlaying and packing difficulties : set hide, vertex hide, self reliant set, and comparable difficulties / Dorit S. Hochbaum -- The primal-dual procedure for approximation algorithms and its program to community layout difficulties / Michel X. Goemans and David P. Williamson -- lower difficulties and their program to divide-and-conquer / David B. Shmoys -- Approximation algorithms for locating hugely hooked up subgraphs / Samir Khuller -- Algorithms for locating low measure constructions / balajirainbow Raghavachari -- Approximation algorithms for geometric difficulties / Marshall Bern and David Eppstein -- numerous notions of approximations : solid, greater, top, and extra / Dorit S. Hochbaum -- Hardness of approximations / Sanjeev Arora and Carsten Lund -- Randomized approximation algorithms in combinatorial optimization / Rajeev Motwani, Joseph (Seffi) Naor, and Prabhakar Raghavan -- The Markov chain Monte Carlo technique : an method of approximate counting and integration / Mark Jerrum and Alistair Sinclair -- on-line computation / Sandy Irani and Anna R. Karlin
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Extra resources for Approximation Algorithms for NP-Hard Problems
Hence, it is worth describing in this section a time-line for the evolution of information systems, since this highlights how data processing has developed and has been used within companies. Digital computers made their appearance in the late 1940s, and soon began to be applied in the business environment. The first decades saw a rush toward information technology development, usually under the mantra of data processing. They were characterized by the widespread diffusion of applications that achieved an increase in efficiency by automating routine operations within companies, especially in administration, production, research and development.
As can be imagined, this abstract definition of system can be used to describe a broad class of real-world phenomena. For example, the logistic structure of an enterprise is a system that receives as input a set of materials, services and information and returns as output a set of products, services and information. More generally, even an enterprise, taken as a whole or in part, may be represented in its turn as a system, provided the boundaries as well as input and output flows are clearly defined.
This brought about the concepts of data warehouses and data marts, which will be described in Chapter 3. Finally, toward the end of the 1990s, the term business intelligence began to be used to generally address the architecture containing DSSs, analytical methodologies and models used to transform data into useful information and knowledge for decision makers, as discussed in Chapter 1. 4 Definition of decision support system Since the late 1980s, a decision support system has been defined as an interactive computer system helping decision makers to combine data and models to solve semi-structured and unstructured problems.
Approximation Algorithms for NP-Hard Problems by Dorit Hochbaum