The first line creates a new AMPL object with all default settings, the second, which is the preferred way to access AMPL options, gets the value of the option version from AMPL as a string and prints the result on the active console. The following lines use the method ampl. Read to load a model and data stored in external AMPL files.
If the files are not found, an exception is thrown. Once these commands are executed, the AMPL interpreter will have interpreted the content of the two files. No further communication is made between the AMPL interpreter and the C object, as every entity is created lazily as needed. Usually, not all the entities are of interest for the programmer. The generic procedure is:. It is a collections of objectives. To access the single instance, the function Get should be used in case of the objective, which gets the only instance of the objective. Since objectives are often single instance, the Value property has been implemented in the class ampl.
So, equivalently to the call above, the following call would return the same value, as it gives direct access to the objective function value totalcost. The input data of an optimisation model is stored in its parameters; these can be scalar or vectorial entities. Two ways are provided to change the value of vectorial parameter: change specific values or change all values at once.
The example shows an example of both ways, reassigning the values of the parameter costs firstly specifically, then altogether. Each time, it then solves the model and get the objective function. The function used to change the values is overloaded, and is in both cases ampl. The code above assigns the values 5.
If the order of the indexing of an entity is known i. A collection of values is assigned to each of the parameter values, in the order they are represented in AMPL. To access all the numeric values contained in a Variable or any other entity, use a ampl. DataFrame object. Doing so, the data is detached from the entity, and there is a considerable performance gain. Often we are interested in very specific values coming out of the optimization session.
To make use of the power of AMPL expressions and avoiding cluttering up the environment by creating entities, fetching data through arbitrary AMPL expressions is possible. For this model, we are interested in knowing how close each decision variable is to its upper bound, in percentage. We can obtain this data into a dataframe using the function ampl.
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GetData with the code :. It is good practice to make sure that the AMPL object is closed and all its resources released when it is not needed any more; the ampl.
AMPL class supoorts the IDisposable interface therefore a using statement guarantees closure of all associated resources. To close the AMPL process at any point in time, refer to the method ampl. Quick search. Read System. C complete reference 1. Herbert Shildt C 2. NET development. It leverages time-tested features withcutting-edge innovations and provides a highly usable, efficient way to write programs for themodern enterprise computing environment. It is, by any measure, one of the most importantlanguages of the 21st century.
The purpose of this chapter is to place C into its historical context, including the forces thatdrove its creation, its design philosophy, and how it was influenced by other computer languages. This chapter also explains how C relates to the. NET Framework. As you will see, C and the. NET Framework work together to create a highly refined programming environment. Rather, they relate to one another, with each newlanguage influenced in one form or another by the ones that came before. In a process akin tocross-pollination, features from one language are adapted by another, a new innovation isintegrated into an existing context, or an older construct is removed.
In this way, languagesevolve and the art of programming advances. C is no exception.
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C inherits a rich programming legacy. It is closely related to another: Java. Understandingthe nature of these relationships is crucial to understanding C. Thus, we begin our examinationof C by placing it in the historical context of these three languages. Whilesome earlier languages, most notably Pascal, had achieved significant success, it was C thatestablished the paradigm that still charts the course of programming today.
C grew out of the structured programming revolution of the s. Structured languages addressed this problem by adding well-definedcontrol statements, subroutines with local variables, and other improvements. Using structuredlanguages, it became easier to write moderately large programs. Although there were other structured languages at the time, C was the first to successfullycombine power, elegance, and expressiveness.
Its terse yet easy-to-use syntax, coupled with itsphilosophy that the programmer not the language was in charge, quickly won many converts. As a result, C became the most widely used structuredprogramming language of the s. However, even the venerable C language had its limits.
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Once a project reaches a certain size, itcan become difficult to understand and maintain. Precisely where this limit is reached depends 3. To solve this problem, a new wayto program began to emerge. This method is called object-oriented programming OOP.
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UsingOOP, a programmer could handle much larger programs. The trouble was that C, the mostpopular language at the time, did not support object-oriented programming. Most of the additions that Stroustrup made to C were designed to support object-oriented programming. Instead of having to learnan entirely new language, a C programmer needed to learn only a few new features beforereaping the benefits of the object-oriented methodology. By the end of the decade, it had become the most widely used programming language. Instead, it was an enhancement to an already highly successful language.
This approach to language development—beginning with an existing language and moving itforward—established a trend that continues today. Work on Java, which was originallycalled Oak, began in at Sun Microsystems.
follow The innovative aspects of Java were driven not so much by advances in the art of programming although some certainly were , but rather by changes in the computing environment. Prior to themainstreaming of the Internet, most programs were written, compiled, and targeted for a specificCPU and a specific operating system. While it has always been true that programmers like toreuse their code, finding a way to easily port a program from one environment to another took abackseat to more pressing problems. However, with the rise of the Internet, in which manydifferent types of CPUs and operating systems are connected, the old problem of portabilityreemerged with a vengeance.
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To solve the problem of portability, a new language was needed,and this new language was Java. Although the single most important aspect of Java and the reason for its rapid acceptance is itsability to create cross-platform, portable code, it is interesting to note that the original impetus forJava was not the Internet, but rather the need for a platform-independent language that could beused to create software for embedded controllers.
In , it became clear that the issues ofcross-platform portability found when creating code for embedded controllers are alsoencountered when attempting to create code for the Internet. Remember, the Internet is a vast,distributed computing universe in which many different types of computers live.
The sametechniques that solved the portability problem on a small scale could be applied to the Internet ona large scale. Therefore,a Java program could run in any environment for which a JVM was available. Also, since theJVM is relatively easy to implement, it was readily available for a large number of environments. Machine code is tied to a specific CPU and operatingsystem. Not only was this impractical, it was expensive. It was also a solution that C would adapt for its own purposes. Furthermore, because Java built upon and improved anexisting paradigm, Gosling, et al.