![]() Of course, Mosel’s data structures and data handling capabilities are a lot more powerful than what is presented in the example. Finally, some aspects of the solution are written to the standard output. The minimize statement calls on the optimizer to solve the problem. There are comments (lines that begin with exclamation point !) describing each type of constraint. Following the initialization block, there are a number of statements that define the problem constraints. The initializations block indicates that the problem data is read from an external file. The shipped quantities and the decision whether to open a facility at a candidate location are arrays of type mpvar, a specialized type to define mathematical programming variables. The cost, capacity and demand data structures are declared as integer arrays indexed with the sets of cities. The sets with the cities are declared as constant sets of string as they are populated with string data. The declarations block defines the objects in the model. The statement uses “mmxprs” specifies that the functionality from the module Xpress-Optimizer is used in this code. The Mosel code defines and solves a capacitated facility location model where the demand in a set of DemandCities must be satisfied from facilities to be located in a set of candidate Suppl圜ities, while minimizing the sum of transportation costs and the fixed costs associated with open facilities. The accompanying lines (see box) provide an example of Mosel code. The statements that specify a model’s variables and constraints closely resemble the usual notation to describe optimization models. The Mosel LanguageĬODING IN MOSEL is straightforward enough if you have some experience with other high-level programming languages. The Mosel libraries provide a simple and efficient device for an organization to integrate sophisticated optimization models with the rest of its information systems. NET library to the existing C/C++, Java, and VB libraries. Once a Mosel model has been built and tested in Xpress-IVE, it may be accessed and executed from other applications through Mosel libraries. This visual environment has many facilities for model debugging, solution analysis and solution display that bolster the productivity of the development effort. Mosel models are typically developed within the graphical user interface Xpress-IVE. This characteristic makes XpressMosel an exciting and virtually limitless environment for optimization-centered applications. For example, calls to external functions and procedures of existing specialized solvers and other programs can be turned into simple Mosel statements. Mosel has a native interface that is defined as public, allowing anyone to enrich the functionality of the language by creating new modules. And because the architecture of Xpress-Mosel was designed to be open and modular, the syntax of the Mosel language can be naturally extended. In Mosel, it is normal to alternate modeling and solving statements to program specialized solution algorithms or any application that is centered in an optimization model. This is in contrast with other algebraic modeling languages like AMPL and OPL, which rely on scripting to perform operations around the model specification. As such, the Mosel language is at the same time an algebraic modeling language and also a true high-level programming language. Mosel is conceived as a programming environment for both modeling and solving optimization problems. In addition to the Xpress-Optimizer, the Xpress-MP suite contains an innovative modeling tool in the form of the Xpress-Mosel component. Experience with time-critical applications, with large-scale linear programs and with tough integer problems has earned Xpress-Optimizer a reputation among practitioners and academicians for being second to none in terms of speed and reliability. The latest release has speed improvements to the algorithms, and it also has added parallel MIP for multi-processing machines. The solvers implemented in the Xpress-Optimizer – a central component of the Xpress-MP suite – benefit from many search-accelerating techniques like presolve algorithms, use of global variables, advanced cutting planes strategies, heuristics, and customizable node and variable selection strategies. ![]() Every new release has continued to expand the state-of-the-art for mathematical programming commercial solvers. Since its inception, Xpress-MP has distinguished itself for fulfilling the efficient implementation of algorithms to solve linear and mixed-integer programming (MIP) problems. THE NEW RELEASE 2005A OF XPRESS-MP adds a number of enhancements to an already impressive suite of optimization and modeling software.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |