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Let's consider the five steps of the OR methodology in more detail:
 
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Operations Research MethodologySolving an Operations Research (OR) problem is not a linear process, but the process can be broken down into five general steps:  
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< Ready to Review > Operations Research MethodologySolving an Operations Research (OR) problem is not a linear process, but the process can be broken down into five general steps:  
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< Ready to Review > Operations Research MethodologySolving an Operations Research (OR) problem is not a linear process, but the process can be broken down into five general steps:  
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Operations Research MethodologySolving an Operations Research (OR) problem is not a linear process, but the process can be broken down into five general steps:  
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However, there are often "feedback loops" within this process. For example, after modelling and solving an OR problem, you will often want to consider the validity of your solution (often consulting with the person who provided the problem description). If your solution is invalid you may need to alter or update your formulation to incorporate your new understanding of the actual problem.  
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Operations Research Methodology  
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Let's consider the five steps of the OR methodology in more detail:
 
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Operations Research MethodologySolving an Operations Research (OR) problem is not a linear process, but the process can be broken down into five general steps:  
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However, there are often "feedback loops" within this process. For example, after modelling and solving an OR problem, you will often want to consider the validity of your solution (often consulting with the person who provided the problem description). If your solution is invalid you may need to alter or update your formulation to incorporate your new understanding of the actual problem.
All the case studies on this TWiki (should!) follow the OR methodology. The Problem Description and Problem Formulation sections correspond to steps 1. and 2. respectively. The Computational Model section shows how some OR software was used to solve the problem, the Results section contains the solution and the analysis and the Conclusion section presents the solution and analysis.  
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< <  TheYou may have already seen This process is shown in the _Operations Research Methodology Diagram_. Note that we have altered the original diagram (from STATS 255) to reflect the use of AMPL. In ENGSCI 255 and STATS 255 you are taught mostly about the _Modeling Process_. The modeling process starts with a welldefined model description, then uses mathematics to formulate a mathematical programme. Next, the modeler enters the mathematical programme into some solver software, e.g., Excel or Storm, and solves the model. Finally, the solution is translated into a decision in terms of the original model description. Using AMPL (or another mathematical programming language) gives you a "shortcut" through the modeling process. By formulating the mathematical programme in AMPL you have already put it into a form that can be used easily by many solvers, e.g., CPLEX, MINOS, so you don't need to enter the mathematical programme into the solver software. However, you usually don't put any "hard" numbers into your formulation, instead you "populate" your model using data files, so there is some work involved in creating the appropriate data file. The advantage of using data files is that the same model may used many times with different data sets (see The AMPL Process for more detail). The Modeling ProcessThe modeling process is a "neat and tidy" simplification of the optimisation process. Let's consider the five steps of the optimisation process in more detail:
 
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< <  Solving an optimisation problem is not a linear process, but the process can be broken down into five general steps:
However, there are often "feedback loops" within this process. For example, after formulating and solving an optimisation problem, you will often want to consider the validity of your solution (often consulting with the person who provided the problem description). If your solution is invalid you may need to alter or update your formulation to incorporate your new understanding of the actual problem. This process is shown in the Operations Research Methodology Diagram. Note that we have altered the original diagram (from STATS 255) to reflect the use of AMPL. In ENGSCI 255 and STATS 255 you are taught mostly about the Modeling Process. The modeling process starts with a welldefined model description, then uses mathematics to formulate a mathematical programme. Next, the modeler enters the mathematical programme into some solver software, e.g., Excel or Storm, and solves the model. Finally, the solution is translated into a decision in terms of the original model description. Using AMPL (or another mathematical programming language) gives you a "shortcut" through the modeling process. By formulating the mathematical programme in AMPL you have already put it into a form that can be used easily by many solvers, e.g., CPLEX, MINOS, so you don't need to enter the mathematical programme into the solver software. However, you usually don't put any "hard" numbers into your formulation, instead you "populate" your model using data files, so there is some work involved in creating the appropriate data file. The advantage of using data files is that the same model may used many times with different data sets (see The AMPL Process for more detail). The Modeling ProcessThe modeling process is a "neat and tidy" simplification of the optimisation process. Let's consider the five steps of the optimisation process in more detail:
 
> >  Operations Research MethodologySolving an Operations Research (OR) problem is not a linear process, but the process can be broken down into five general steps:
However, there are often "feedback loops" within this process. For example, after modelling and solving an OR problem, you will often want to consider the validity of your solution (often consulting with the person who provided the problem description). If your solution is invalid you may need to alter or update your formulation to incorporate your new understanding of the actual problem. All the case studies on this TWiki (should!) follow the OR methodology. The Problem Description and Problem Formulation sections correspond to steps 1. and 2. respectively. The Computational Model section shows how some OR software was used to solve the problem, the Results section contains the solution and the analysis and the Conclusion section presents the solution and analysis. You may have encountered parts of the OR methodology in introductory OR classes ( link: ??? Mike to link to ENGSCI 255/STATS 255 ??? ). The Modelling Process
TheYou may have already seen This process is The Modeling ProcessThe modeling process is a "neat and tidy" simplification of the optimisation process. Let's consider the five steps of the optimisation process in more detail:
 
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However, there are often "feedback loops" within this process. For example, after formulating and solving an optimisation problem, you will often want to consider the validity of your solution (often consulting with the person who provided the problem description). If your solution is invalid you may need to alter or update your formulation to incorporate your new understanding of the actual problem. This process is shown in the Operations Research Methodology Diagram. Note that we have altered the original diagram (from STATS 255) to reflect the use of AMPL. In ENGSCI 255 and STATS 255 you are taught mostly about the Modeling Process. The modeling process starts with a welldefined model description, then uses mathematics to formulate a mathematical programme. Next, the modeler enters the mathematical programme into some solver software, e.g., Excel or Storm, and solves the model. Finally, the solution is translated into a decision in terms of the original model description. Using AMPL (or another mathematical programming language) gives you a "shortcut" through the modeling process. By formulating the mathematical programme in AMPL you have already put it into a form that can be used easily by many solvers, e.g., CPLEX, MINOS, so you don't need to enter the mathematical programme into the solver software. However, you usually don't put any "hard" numbers into your formulation, instead you "populate" your model using data files, so there is some work involved in creating the appropriate data file. The advantage of using data files is that the same model may used many times with different data sets (see The AMPL Process for more detail). The Modeling ProcessThe modeling process is a "neat and tidy" simplification of the optimisation process. Let's consider the five steps of the optimisation process in more detail:
 MichaelOSullivan  16 Feb 2008 