Optimization problems are not only formed into a linear programming but also nonlinear programming. In real life, often decision variables restricted on integer. Hence, came the nonlinear programming. One particular form of nonlinear programming is a convex quadratic programming which form the objective function is quadratic and convex and linear constraint functions. In this research designed ...

In this paper, I argue that the programming languages provided in current mainstream CASes are not suitable for general purpose programming. To address this problem, I developed MrMathematica. MrMathematica is a connection between Mathematica and PLT-Scheme, which provides the ability to call Mathematica from MzScheme. The two languages share some common ground, but are mostly complementary to ...

This paper presents new and ongoing development efforts directed toward open-source, cross-platform C++ “tools” for music and audio programming. RtMidi provides a common application programming interface (API) for realtime MIDI input and output on Linux, Windows, Macintosh, and SGI computer systems. RtAudio provides complementary functionality for realtime audio input and output streaming. The ...

This paper describes work undertaken to incorporate agents that can learn into an existing multi-agent system, designed to advise on good programming practice. The power of this approach is that the learning agents within the system can adapt domain knowledge to evolve programming standards over time. A prototype system has been developed which uses multiple agents to embody complementary learn...

Inductive Logic Programming can be used to provide automated support to help correct the errors identified by model checking, which in turn provides the relevant context for learning hypotheses that are meaningful within the domain of interest. Model checking and Inductive Logic Programming can thus be seen as two complementary approaches with much to gain from their integration. In this paper ...

We give two categorical programming languages with variable arrows and associated abstraction/reduction mechanisms, which extend the possibility of categorical programming Hag87, CF92] in practice. These languages are complementary to each other { one of them provides a rst-order programming style whereas the other does higher-order { and are \children" of the simply typed lambda calculus in th...

Because of their complementary strengths, optimization and constraint programming can be profitably merged. Their integration has been the subject of increasing commercial and research activity. This paper summarizes and contrasts the characteristics of the two fields; in particular, how they use logical inference in different ways, and how these ways can be combined. It sketches the intellectu...

The problem of determining whether quadratic programming models possess either unique or multiple optimal solutions is important for empirical analyses which use a mathematical programming framework. Policy recommendations which disregard multiple optimal solutions (when they exist) are potentially incorrect and less than efficient. This paper proposes a strategy and the associated algorithm fo...

Dynamic software adaptability is one of the central features leveraged by autonomic computing. However, developing software that changes its behavior at run time adapting to the operational conditions is a challenging task. Several approaches have been proposed in the literature to attack this problem at different and complementary abstraction levels: software architecture, middleware, and prog...

Sequential programming and work-flow programming are two useful, but radically different, ways of describing computational processing. Of the two, it is sequential programming that we teach all programmers and support by programming languages, whether in procedural, objectoriented, or functional paradigms. We teach workflow as a secondary style of problem decomposition for use in special situat...