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# Business Management, Operations Research, and Financial Engineering Research

(The University of Hong Kong)

### - Overview

Operations research (OR) is a discipline that deals with the application of advanced analytical methods to help make better decisions. OR often considered to be a sub-field of mathematical sciences. Disciplines that are similar to, or overlap with, OR includes statistical analysis, management science, game theory, optimization theory, artificial intelligence and network analysis. All of these techniques have the goal of solving complex problems and improving quantitative decisions.

The field of OR provides a more powerful approach to decision making than ordinary software and data analytics tools. Employing OR professionals can help companies achieve more complete datasets, consider all available options, predict all possible outcomes and estimate risk. Additionally, OR can be tailored to specific business processes or use cases to determine which techniques are most appropriate to solve the problem.

### - Characteristics of Operations Research (OR)

Employing techniques from other mathematical sciences, such as mathematical modeling, statistical analysis, and mathematical optimization, OR arrives at optimal or near-optimal solutions to complex decision-making problems. Because of its emphasis on human-technology interaction and because of its focus on practical applications, OR has overlap with other disciplines, notably industrial engineering and operations management, and draws on psychology and organization science. OR is often concerned with determining the extreme values of some real-world objective: the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost).

Originating in military efforts before World War II, its techniques have grown to concern problems in a variety of industries. There are three primary characteristics of all OR efforts:

• Optimization: The purpose of OR is to achieve the best performance under the given circumstances. Optimization also involves comparing and narrowing down potential options.
• Simulation: This involves building models or replications in order to try out and test solutions before applying them.
• Probability and statistics: This includes using mathematical algorithms and data to uncover helpful insights and risks, make reliable predictions and test possible solutions.

[New York City, New York - Civil Engineering Discoveries]

### - Management Science

In 1967 Stafford Beer characterized the field of management science as "the business use of operations research". Like operational research itself, 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. Management scientists help businesses to achieve their goals using the scientific methods of operational research.

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.

Management science is concerned with developing and applying models and concepts that may prove useful in helping to illuminate management issues and solve managerial problems, as well as designing and developing new and better models of organizational excellence.

The application of these models within the corporate sector became known as management science.

### - Applications of Operations Research and Management Science

Applications are abundant such as in airlines, manufacturing companies, service organizations, military branches, and government. The range of problems and issues to which it has contributed insights and solutions is vast. It includes:

• Scheduling (of airlines, trains, buses etc.)
• Assignment (assigning crew to flights, trains or buses; employees to projects; commitment and dispatch of power generation facilities)
• Facility location (deciding most appropriate location for new facilities such as warehouse; factory or fire station)
• Hydraulics & Piping Engineering (managing flow of water from reservoirs)
• Health Services (information and supply chain management)
• Game Theory (identifying, understanding; developing strategies adopted by companies)
• Urban Design
• Computer Network Engineering (packet routing; timing; analysis)
• Telecom & Data Communication Engineering (packet routing; timing; analysis)

Management is also concerned with so-called 'soft-operational analysis' which concerns methods for strategic planning, strategic decision support, problem structuring methods. In dealing with these sorts of challenges, mathematical modeling and simulation may not be appropriate or may not suffice. Therefore, during the past 30 years[vague], a number of non-quantified modeling methods have been developed. These include:

• stakeholder based approaches including metagame analysis and drama theory
• morphological analysis and various forms of influence diagrams
• cognitive mapping
• strategic choice
• robustness analysis

### - Financial Engineering

Financial engineering is the use of mathematical techniques to solve financial problems. Financial engineering uses tools and knowledge from the fields of computer science, statistics, economics, and applied mathematics to address current financial issues as well as to devise new and innovative financial products.

[More to come ...]