What are the 3 types of software?--Computers are managed by software. Software may be divided into three categories: system, utility, and application.
What is the difference between download and install?--The act of "downloading" a file is distinct from "installing" it. Instructions to utilize the downloaded data to modify your computer are "installing" the file. The file does not alter or be updated if installation is not performed.
What is software used for?--Software is a collection of instructions, data, or computer programs used to run machines and carry out certain activities. It is the antithesis of hardware which refers to a computer external components. A device running programs, scripts, and applications are collectively referred to as "software" in this context.
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Mo-ps is a simple but powerful project management tool for easy creating and tracking of dynamic project schedules. Tasks are automatically scheduled by the availability of the assigned resources and can be grouped hierarchically. Dependencies are supported and critical paths displayed. The application is highly scalable, also huge projects with several thousands of tasks and hundreds of resources can be processed without a loss of performance. Team development is supported by locking parts of shared projects. Further features are: Reusable individual calendars; Unlimited powerful undo/redo; VBA scripting interface with full access to the project database; Unicode support; Html publishing of plans.MOPS stands for Mathematical Optimization Systems, MOPS is an optimization software system design to solve linear and integer mathematical programming problems. It has been in continual development since 1987 by Prof. Uwe Suhl. MOPS for MPL gives users access to this highly regard optimizer from within the user-friendly Windows environment of MPL.
The MOPS solver includes efficient solution methods for linear and mixed-integer optimization models. Incorporation of good preprocessing techniques for both LP and MIPs makes it useful in tackling large range of LP and MIP problems. MOPS Simplex Optimizers includes fast and robust implementations of both the Primal and Dual Simplex methods. It incorporates a number of pricing options including Devex and Steepest edge pricing. MOPS also have a state of the art interior point method that is highly beneficial is solving large linear programming problems or problems that tend to be highly degenerate. MOPS Barrier solver provides an alternative means of solving linear models. The Barrier option utilizes a barrier or interior point method to solve linear models. Unlike the Simplex solvers that move along the exterior of the feasible region, the Barrier solver moves through the interior space to find the optimum. Depending upon the size and structure of a particular model, the Barrier solver may be significantly faster than the Simplex solvers and can provide exceptional speed on large linear models, particularly on sparse models with more than 5,000 constraints or highly degenerate models. MOPS Integer Optimizer contains sophisticated branch and bound algorithmic techniques to solve problems that contain general and/or binary integer restrictions. It is equipped with advanced supernode processing. It has a large collection of cutting plane algorithms that can drastically reduce the search space.
Mops is an advanced modeling system that allows the model developer to formulate complicated optimization models in a clear, concise, and efficient way. Models developed in mops can then be solved with any of the multiple commercial optimizers available on the market today. mops includes an algebraic modeling language that allows the model developer to create optimization models using algebraic equations. The model is used as a basis to generate a mathematical matrix that can be relayed directly into the optimization solver. This is all done in the background so that the model developer only needs to focus on formulating the model. Algebraic modeling languages, such as mops, have proven themselves over the years to be the most efficient method of developing and maintaining optimization models because they are easier to learn, quicker to formulate and require less programming.
mops offers a feature-rich model development environment that takes full advantage of the graphical user interface in Microsoft Windows, making mops a valuable tool for developing optimization models. mops can import data directly from databases or spreadsheets. Once the model has been solved, MPL also has the ability to export the solution back into the database. mops models can be embedded into other Windows applications, such as databases or spreadsheets, which makes mops ideal for creating end-user applications.
The mops Modeling System is a state-of-the-art optimization modeling software. mops, through the use of advanced graphical user interface features, creates a flexible working environment that enables the model developer to be more efficient and productive. mops provides in a single system all the essential components needed to formulate the model, gather and maintain the data, optimize the model, and then analyze the results.
The model developer uses the built-in model editor to formulate the mops model statements and then selects the optimizer directly from the menus to solve the model. The solution results are automatically retrieved from the solver and displayed, providing the user with instant feedback. Each item defined in the model is also displayed in a tree window allowing the model developer to browse through them easily.
When using mops to work on multiple models, the user can manage them effectively by utilizing project files. Project files store information about items such as, open model files and windows, the default working directory, and current option settings for both the modeling system and the solver.
The mops Modeling System links to solvers dynamically through memory at run-time. This gives mops the capability to integrate the solver completely into the modeling environment, resulting in the matrix being transferred between the modeling system and the solver directly through memory. As no files are involved, this seamless connection is both considerably faster and more robust than the traditional use of files in other modeling systems. In the event it is necessary to change any algorithmic options, mops provides easy-to-use option dialog boxes for each solver. mops fully supports context-sensitive help for option dialog boxes. A complete, printable on-line version of the manual, covering both the modeling environment and the language, is also available in the on-line help system for easy access.
mops was designed to be portable and to be run on multiple platforms. mops for Windows is the most popular platform but an OSF Motif version is also available for various UNIX flavors including: HP 9000, IBM RS-6000, Sun SPARC, and Silicon Graphics. mops models are portable so a model created for one platform can always be read on any other supported platform. The mops Modeling Language offers a natural algebraic notation that enables the model developer to formulate complex optimization models in a concise, easy-to-read manner. Among modeling languages, mops is unrivaled in its expressive power, readability, and user-friendliness. The mops Modeling Language was designed to be very easy to use with a clear syntax making the process of formulating models in mops efficient and productive. mops is a very flexible language and can be used to formulate models in many different areas of optimization ranging from production planning, scheduling, finance, and distribution, to full-scale supply-chain optimization.
mops is a very robust and stable software whose core modules have been through extensive use and testing over more than a decade. This assures that the mops software is both reliable and dependable and can be used in mission-critical projects. Some of the more notable features of the mops language include:
One of the most important features of any modeling language is how it handles large amounts of data. What makes mops so powerful is its ability to effectively handle very large sparse index and data sets. In addition, mops has extensive flexibility when working with subsets of indexes, functions of indexes, and compound or multi-dimensional index sets. This allows the model formulator, for example, to index only over products that are made by each machine in a specific plant instead of having to go through all the products for all the machines and all the plants, which would be considerable slower. mops can easily handle very large matrices with millions of variables and constraints. This is especially important when dealing with large supply-chain optimization models over multiple time periods that can grow very quickly. mops has its own memory manager that can dynamically store models of any size, giving it a full scalability. The only limitation the model developer faces is how much memory is available on his or her machine. Typically, mops uses only 1-2MB of memory per 10,000 variables, which puts a minimal additional burden on the machine capacity needed to generate and solve the matrix.
The matrix generation in mops is extremely fast and efficient which is important since it contributes to the overall time needed to obtain the solution of the model. Maximal has over the years invested significant R&D efforts on continuing to improve the speed of the matrix generation. As a result, we can now run models with millions of variables and generate a matrix for them in less than one minute. This is very important, because if the matrix generation takes too long it can seriously add to the time needed to reach the solution even if the fastest optimization solvers are used. mops provides the fastest and most scalable matrix generation capabilities available in a modeling system on the market today.
Importing data from a variety of corporate database systems into optimization models is frequently an essential requirement for optimization projects. One of the advanced features of mops is the database connection option that directly links mops with relational databases and other data sources. This option enables the model developer to gather both indexes and data values from various data sources and import them directly into the model. After the model has been optimized, the solution output can be exported back into the database. This, along with the run-time features of mops, allows the model developer to easily create customized end-user applications for optimization using the built-in data entry and reporting capabilities of the database.
The database connection in mops has the ability to access data from many different sources, such as databases, Excel spreadsheets, external data files, and the Internet. This gives the model developer the flexibility to choose the most efficient and convenient way to incorporate the data into the model. Among the data formats that are supported by mops are: Microsoft Access and Excel, ODBC, Paradox, FoxPro, Dbase, SQL Server, and Oracle.
This new version of mops provides, in a single system, all the essential components needed to formulate the model, gather and maintain the data, optimize the model, and then analyze the results. With mops, you can now achieve a quantum leap in your productivity as a model developer.
- Separation of the data from the model formulation
- import data from different data sources
- Independence from specific solvers
- Use of macros for repetitive parts of the model
- Exclusion of parts of the model using conditional directives
- Special Ordered Sets and Semi-continuous variables
- WHERE/IF conditions to handle special cases
- Readable and helpful error messages