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Optimized software can provide powerful technologies to improve efficiency and profits. In actuality, however, it requires powerful mathematical engines, execution engines, efficient models, and flexible applications. The IBM ILOG CPLEX Studio provides methods to quickly construct effective optimization models for any planning and scheduling problems. Through complete integrated development environments, overall optimization application development processes are supported for data integration and conversion, debugging, tuning, and assignment.
IBM ILOG CPLEX
IBM ILOG CP Optimizer
The IBM ILOG CPLEX Studio modeling script can express optimization models realistically with much less effort than commonly used programming languages. The data structure of the optimization problem is defined to provide modeling techniques that naturally connect the decision-making variables, goal formula, and constraint formulas.
In IBM ILOG CPLEX Studio OR, experts utilize various approach methods to easily find the values for a problem. Debugging and tuning tools provide support so that developers can improve the model. The developed model proceeds through external applications made with Java, .Net or C++ or can be generated with IBM ILOG ODM applications.
IBM ILOG CPLEX Studio is closely integrated with IBM ILOG ODM to generate initial applications including dialogue-type decision-making UI through simple wizard guidance.
Regardless of which stage the model development process is in, the initial model can be converted into practical application prototypes. Business analysts and managers can easily understand and utilize input/output and can participate in improvements such as models, displays, scenario generation parameter, and model activation.
Using the IBM ILOG JView-based chart, the developer can easily express useful information needed for comparing solution analyses and scenarios. In addition, it also offers editors to edit display tables and charts, business goals, business expression and constraint expression activations.
Optimization technology that leads the market
Decision-makers of companies must continuously analyze their management factors to search for new methods to realize efficiency and profit improvements. Economic planning and operational scheduling must take into consideration various strategies, expenses, operating constraint conditions, business presumptions, unforeseen incidents, time constraints, and customer service demand conditions. Fortunately, mathematical programming (MP) and optimization technologies can help make this happen. The IBM ILOG CPLEX makes it possible to resolve complex business problems that cannot be solved with the human brain alone or the latest spreadsheets.
IBM ILOG CPLEX is used in airport networks, production plans, portfolio management, and employee scheduling. Major companies and software providers for the manufacturing, finance, transportation and logistics, facility, national defense, and other industrial sectors have adopted IBM ILOG CPLEX in their wide-range applications. In fact, 30% of the global top 500 companies, and over 1,000 companies and 500 college research teams depend on the powerful problem-solving capacities of IBM ILOG CPLEX that cannot be compared with any other product.
IBM ILOG CPLEX can solve major problems on site at surprising speeds. It has already distributed thousands of its products worldwide, proving its reliability and safety. Developers can access its powerful performance through the library designed to be integrated with IBM ILOG CPLEX.
Simplex Optimizer
Barrier Optimizer
MIP Solver
Parallel Solver
IBM ILOG CPLEX offers flexible high performance optimizes to solve LP, MILP, MIQP, and MIQCP. New performance records are continuously being set in the mathematical programming sector. IBM ILOG has been recognized in the OR sector for its performance, reliability, and usability through continuous improvements.
Optimal automation constraint programming optimizer
Important optimization problems such as deciding work sequence, packaging, time tabling, and additional problems of column generation are too irregular to be solved by MP (Math Programming). Solving by MP is not appropriate for these problems due to nonlinear constraints or fractional mathematic formulas. IBM ILOG CP Optimizer constructs broad-range modeling and uses search processes utilizing constraint propagation methods to provide optimal solutions to general business issues such as resource allotment, production sequence decision, time tabling, and employee scheduling.
Typical CP (Constraint Programming) engines must designate models and search strategies necessary for problem solving. IBM ILOG CP Optimizers are similar in terms of methods that the IBM ILOG CPLEX uses, but is designed to support simpler model and run development processes. The powerful solution search engine can immediately discover feasible solutions, and when better solutions cannot be found, the solution is improved upon. For the first time, CP technologies can use complex problems without search command programming. It has become possible to provide the same user convenience as that provided when the IBM ILOG XPLEX solves MP model problems.
IBM ILOG CP Optimizer can solve problems in the actual world at surprising speeds. This solution search engine accepts the peculiar characteristics of scenario data and models to help the application offer excellent response times.
Computation constraints
Logic constraints
Sequence-based constraints
Tunable optimization
Prompt generation of realizable solutions
Model and Run development process
IBM ILOG CP Optimizer provides comprehensive modeling composition. In other words, computation constrains and formulas (e.g. sum, product, max, min, abs, modulo, division, different, equality), logic constraints (e.g. and, or, imply), indexing and commonly used patterns based on sequencing through decision-making variables (each are different and pre-order, inverse order, etc. corresponds to this), and specific constraints for simple and efficient expressions correspond to this. Through such expressions, the most complex problems are expressed as simple and efficient models, and support is provided to add new additional constraint conditions without editing the basic data structure.
The IBM ILOG CP Optimizer automatically establishes search strategies suitable to the proposed model and data, and then provides options that can strategically adjust construction or parameters that are especially emphasized in individual algorithms or constraint condition propagation methods.
The solution search technology of IBM ILOG CP Optimizer is not only for the optimization of independent CP models. In the case of complex problems, the IBM ILOG CPLEX and IBM ILOG CP Optimizer can be combined for use. Cases used in the industry include drafting work shift tables, bin packing, and crew and sports event scheduling.
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