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Home | Analytical Consulting | Operations Research and Management Science
Operations Research and Management Science
The terms Operations Research and Management Science
tend to be used synonymously. Operations research (or operational
research, as it's called in Europe) refers to scientific methods (statistical
and mathematical modeling, experiments, simulation, and optimization) applied
to the solution of complex business problems. Operations research is about deriving
optimal solutions to maximize sales or profits and/or to minimize costs, losses,
or risks.
The basic tools of operations research are probability theory, Monte Carlo
methods, stochastic processes, queuing models, transportation models, network
models, game theory, linear and nonlinear programming, dynamic programming,
Markov decision processes, input-output analysis, choice modeling, econometric
modeling, and other mathematical techniques and algorithms. The ultimate goal
is to create a mathematical model that simulates real-world processes and systems
so that optimal solutions can be found. Computer science technologies and software
development capabilities are often critical components in successful operations
research projects.
- Distribution system optimization. What is the optimal number of warehouses, trucks and routes to minimize out-of-stocks, or minimize distribution
costs or maximize delivery speeds? Where should the warehouses be located? What are the most efficient delivery routes? What size should the trucks be?
How should the products be packaged and palletized for most efficient shipping?
- Retail site selection optimization. Which markets offer
the greatest potential for new retail outlets? What store density maximizes
sales revenue or profits? What’s the interaction between advertising
investments and number of retail units? What sections of a metropolitan area
offer the greatest potential for new retail units? What specific retail locations
will yield the greatest return on investment? What deployment of retail units
minimizes supply chain and distribution costs?
- Store design optimization. What type of store design will
maximize consumer visits, time spent in store, or sales? What elements of
store design are most important to consumers, and what arrangements of these
elements are optimal? How should store design vary to maximize appeal to a
particular demographic target or for a given location? What product mix corresponds
to and supports the optimal store design?
- Store merchandise optimization. What is the optimal mix of merchandise in a given store to maximize sales or profits? How should this
optimal mix vary across different types of geographic areas and demographic groups? How should this product mix vary throughout the business cycle? What
are the optimal marketing elements to support the optimal merchandise mix?
- Retail category optimization. There are many categories
of products within a retail store. Retailers often strive to maximize sales
within each category. What is the optimal mix of brands, sizes, and facings
to increase category sales? Will optimization of one category negatively affect
other categories? How can product categories be optimized without hurting
overall store sales?
- Supply chain optimization. What’s the optimal way
to manage the flow of raw materials, components, and supplies from various
vendors to the manufacturer, under conditions of varying and uncertain demand?
- Manufacturing/Production optimization. What organization,
machines, processes, and work flows will maximize quality, minimize costs,
and maximize output? Optimizing manufacturing processes must be closely integrated
with optimization of the related supply chain and distribution system.
- Network optimization. How should airports be designed to
handle luggage and passenger flow? How should traffic lights be organized
and timed to maximize traffic flow? What is the optimal design of an electrical
grid or a communications network?
- Transportation optimization. What route structure minimizes
the number of trucks, railcars, or school buses needed to achieve a certain
service threshold or minimizes waiting times? Which common carriers provide
the most efficient distribution services for a particular business? How should
these transportation solutions vary as conditions change (weather, time of
day, traffic density, etc.)?
- Scheduling optimization. What type of schedule or scheduling
system will yield the greatest revenue, minimize costs, reduce delivery times,
or meet other objectives? How should scheduling change as conditions and the
business environment change?
- Strategy optimization. What markets, technologies, systems
and processes, products and services, and positioning and messages will achieve
the greatest long-term success for a given brand, business unit, or corporation?
That is, what is the optimal business model for a given company in a given
industry?
- Trading and markets optimization. Some problems can be addressed via artificial markets (e.g., “cap and trade”) wherein
interested parties bid against each other and trade with each other. What is the optimal way to build such a market, and how can the results be evaluated
and understood?
Analytical Consulting Services
Decision Analyst’s strengths in statistics and mathematics, simulation, modeling, and optimization provide the analytical foundation to address complex
business and strategy problems.
If your company is facing tough, complex decisions and wants to improve its
strategy and performance, Operations Research and Management Science offer powerful
analytical tools to help you make the very best decisions. If you would like
to learn more or discuss a specific topic with one of our consultants, please
contact Jerry W. Thomas, President/CEO (jthomas@decisionanalyst.com),
or John Colias, Ph.D., Senior Vice President Advanced Analytics
(jcolias@decisionanalyst.com),
or call 1-800-ANALYSIS (262-5974) or 1-817-640-6166.
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