Can mathematical modeling or quantitative techniques help the manager to solve the problem of work assignment? Rationally support your argument.
Management science (MS) is an interdisciplinary branch of applied mathematics devoted to optimal decision planning, with strong links with economics, business, engineering, and other sciences. It uses various scientific research-based principles, strategies, and analytical methods including mathematical modeling, statistics and numerical algorithms to improve an organization's ability to enact rational and meaningful management decisions by arriving at optimal or near optimal solutions to complex decision problems. The discipline is typically concerned with determining the maxima (of profit, assembly line performance, crop yield, bandwidth, etc) or minima (of loss, risk, costs, etc.) of some objective function. In short, management sciences help businesses to achieve goals using various scientific methods.
The field was traditionally known as Operations research (OR) in the United States and Canada, or operational research in the United Kingdom. These three terms are often used interchangeably to describe the same field.
Management science is concerned with a number of different areas of study:
1) Developing and applying models and concepts that may prove useful in helping to illuminate management issues and solve managerial problems. The models used can often be represented mathematically, but sometimes computer-based, visual or verbal representations are used as well or instead.
2) Designing and developing new and better models of organizational excellence. A leading influence in this area is the work of Dr. Mark Draper which combines insights from the fields of knowledge management, cognitive psychology, leadership training, learning theory, and modern behavioral psychology. Dr. Jim Collins's work at Stanford presents the important scientific facts about how to turn a good organization into a great one. Dr Draper's work focuses more on how to create new powerful and effective organizations.
Management science research can be done on three levels.
Ø The fundamental level lies in three mathematical disciplines: Probability, Optimization, and Dynamical systems theory.
Ø The modeling level is about building models, analyzing them mathematically, gathering and analyzing data, implementing models on computers, solving them, playing with them all this is part of Management Science research on the modeling level. This level is mainly instrumental, and driven mainly by statistics and econometrics.
Ø The application level, just as any other engineering and economics' disciplines, has strong aspirations to make a practical impact and be a driver for change in the real world.
The management scientist's mandate is to use rational, systematic, science-based techniques to inform and improve decisions of all kinds. Of course, the techniques of management science are not restricted to business applications but may be applied to military, medical, public administration, charitable groups, political groups or community groups.
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3D modeling of industrial designs serves to demonstrate engineering solutions, forms, usage, and aesthetics of products with clarity and providing real life three dimensional prototypes. 3D modeling is a mathematical framework of a 3 D object using various structural software and advanced CAD techniques.
The Mathematical Technique of Modeling is Chest/Bust-X Waist-Y Hips-Z ( X - Y - Z ) Example (34-24-34)
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An abstract model is a mathematical model which contains an abstraction.
Mark M. Meerschaert has written: 'Mathematical modeling' -- subject(s): Mathematical models 'Stochastic models for fractional calculus' -- subject(s): Fractional calculus, Diffusion processes, Stochastic analysis 'Mathematical Modeling'
The logistic growth model is a mathematical formula frequently used to predict population fluctuations in a community. It takes into account factors like carrying capacity and growth rate to model how a population grows over time.
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J. C. Frauenthal has written: 'Mathematical modeling in epidemiology' -- subject(s): Epidemiology, Mathematical models
Michael J. Conroy has written: 'Identification and synthetic modeling of factors affecting American black duck populations' -- subject(s): Black duck 'Quantitative conservation of vertebrates' -- subject(s): Conservation biology, Mathematical models, Vertebrate populations
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Nagraj Balakrishnan has written: 'Managerial decision modeling with spreadsheets' -- subject(s): Mathematical models, Management, Management science 'Managerial decision modeling with spreadsheets' -- subject(s): Management, Management science, Mathematical models
Since she is already a celebrity and has a contract with Wilhelmina Models, chances are that she makes a few thousand dollars per modeling assignment or more.