Computer Simulation In Management Science

Computer Simulation in Materials Science

Modelling and Simulation in Management Sciences

This book includes a collection of selected papers presented at the International Conference on Modelling and Simulation in Engineering, Economics, and Management, held at the Faculty of Economics and Business at the University of Girona, Spain, 28-29 June 2018.The conference was organized by the Association for the Advancement of Modelling and Simulation Techniques in Enterprises (AMSE) and the University of Girona with the aim of promoting research in the field of modelling, simulation and management science. This book presents original research studies related to fuzzy logic, soft computing and uncertainty, as well as a number of papers in the field of bibliometrics in social sciences. Presenting new advances in these areas, with a special focus on management, economics and social sciences. It is of great interest to researchers and Ph.D. students working in the field of fuzzy logic, soft computing, uncertainty and bibliometrics.

Current Issues in Computer Simulation

Current Issues in Computer Simulation is a collection of papers dealing with computer simulation languages, statistical aspects of simulation, linkage with optimization and analytical models, as well as theory and application of simulation methodology. Some papers explain the General Purpose Simulation System (GPSS), a programming package incorporating a language to simulate discrete systems; and the SIMSCRIPT, a general-purpose simulation language using English commands, for example, FORTRAN. Another simulation language is the General Activity Simulation Program (GASP), providing for an organizational structure to build models to simulate the dynamic performance of systems on a digital computer. Other papers discuss simulation models of real systems, including corporate simulation models, multistage consumer choice process, determination of maximum occupancy for hospital facilities, and the juvenile court system. Many computer simulations are statistical sampling experiments performed on a model of the system under investigation. Other papers discuss some of the variables involved in the statistical design and analysis of simulation experiments such as variance reduction techniques, generation of random variates, and experimental layout. For example, one application simulates inventory systems when many items are stocked in various locations. The collection is suitable for programmers, computer engineers, businessmen, hospital administrators, schools officials, and depositories of huge volumes of information or data.