00982nam--2200337---450-99000234189020331620090708181715.0000234189USA01000234189(ALEPH)000234189USA0100023418920050107d1965----km-y0itay0103----baengUS||||||||001yyDamages in personal injury and wrongful death casesSol SchreiberNew YorkPracticing Law Institute1965607 p.24 cm20012001001-------2001SCHREIBER,Sol277026ITsalbcISBD990002341890203316XXV.1.M 590 (IG I 251)4311 G.IG I00240127BKGIUSIAV41020050107USA011544RSIAV39020090708USA011817Damages in personal injury and wrongful death cases1062238UNISA04931nam 2200565 450 991081615760332120200520144314.01-119-38706-X1-119-38707-81-119-38705-1(CKB)4100000000641136(Au-PeEL)EBL5015534(CaPaEBR)ebr11430731(CaONFJC)MIL1033389(OCoLC)988749666(CaSebORM)9781119386995(MiAaPQ)EBC5015534(EXLCZ)99410000000064113620170926h20172017 uy 0engurcnu||||||||rdacontentrdamediardacarrierMeta-heuristic and evolutionary algorithms for engineering optimization /Omid Bozorg-Haddad, Mohammad Solgi, Hugo A. Loaiciga1st editionHoboken, New Jersey :Wiley,2017.©20171 online resource (281 pages) illustrationsWiley Series in Operations Research and Management Science1-119-38699-3 Includes bibliographical references and index.Overview of optimization -- Introduction to meta-heuristic and evolutionary algorithms -- Pattern search -- Genetic algorithm -- Simulated annealing -- Tabu search -- Ant colony optimization -- Particle swarm optimization -- Differential evolution -- Harmony search -- Shuffled frog-leaping algorithm -- Honey-bee mating optimization -- Invasive weed optimization -- Central force optimization -- Biogeography-based optimization -- Firefly algorithm -- Gravity search algorithm -- Bat algorithm -- Plant propagation algorithm -- Water cycle algorithm -- Symbiotic organisms search -- Comprehensive evolutionary algorithm.A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irriga...Wiley series in operations research and management science.Mathematical optimizationEngineering designMathematicsMathematical optimization.Engineering designMathematics.620/.0042015196Bozorg-Haddad Omid1974-1051360Solgi MohammadLoaiciga Hugo A.MiAaPQMiAaPQMiAaPQBOOK9910816157603321Meta-heuristic and evolutionary algorithms for engineering optimization4088511UNINA02005nam 22003973a 450 991076579320332120250203235642.097888927396118892739611https://doi.org/10.26530/OAPEN_356380(CKB)5400000000000367(ScCtBLL)7cbedad2-b965-4ce4-828a-6bc42cd825a0(OCoLC)1163845928(EXLCZ)99540000000000036720250203i20062020 uu itauru||||||||||txtrdacontentcrdamediacrrdacarrier3.1 Etica di impresa : Considerazioni teoriche ed evidenze tecniche /Debora Ninci, Cristiano Ciappei[s.l.] :Firenze University Press,2006.1 online resource (1 p.)This book proposes theoretical reflections, tools and techniques for a business ethic that aims at the construction of social welfare. A correct connotation of business ethics is seen in its role of interface between the ontology of the "enterprise phenomenon" and the social ethics of its operation. The book upholds the theory that business development can be such only if it leads to the emancipation of the persons affected by the same. A development in which, that is, it is not only the economic results that have bearing, but above all the way in which they are obtained and exploited. In enterprise, too, priority should hence be given to a practice implemented in a conscientious manner which enhances the complete development of the persons involved, whether they are workers or consumers.Business & Economics / Business EthicsbisacshEconomicsBusiness & Economics / Business EthicsEconomics.Ninci Debora501588Ciappei CristianoScCtBLLScCtBLLBOOK99107657932033213.1 Etica di impresa4319264UNINA