We extend the Constraint Logic Programming (CLP) formalism in order to handle semiring-based constraint systems. This allows us to perform in the same language both constraint solving and optimization. In fact, constraint systems based on semirings are able to model both classical constraint solving and more sophisticated features like uncertainty, probability , fuzzyness, and optimization. We ...

We extend the Constraint Logic Programming (CLP) formalism in order to handle semiringbased constraint systems. This allows us to perform in the same language both constraint solving and optimization. In fact, constraint systems based on semirings are able to model both classical constraint solving and more sophisticated features like uncertainty, probability, fuzzyness, and optimization. We th...

‎This paper proposes a new form of optimization problem which is a two-level programming problem with infinitely many lower level constraints‎. ‎Firstly‎, ‎we consider some lower level constraint qualifications (CQs) for this problem‎. ‎Then‎, ‎under these CQs‎, ‎we derive formula for estimating the subdifferential of its valued function‎. ‎Finally‎, ‎we present some necessary optimality condit...

The most important issue in multi-objective optimization problems is to determine the Pareto points along the Pareto frontier. If the optimization problem involves multiple conflicting objectives, the results obtained from the Pareto-optimality will have the trade-off solutions that shaping the Pareto frontier. Each of these solutions lies at the boundary of the Pareto frontier, such that the i...

Structural reliability theory allows structural engineers to take the random nature of structural parameters into account in the analysis and design of structures. The aim of this research is to develop a logical framework for system reliability analysis of truss structures and simultaneous size and geometry optimization of truss structures subjected to structural system reliability constraint....

In this work, we report the experimental implementation of a Quantitative Feedback Theory (QFT) based robust controller, designed online using hybrid global optimization and constraint propagation techniques. The hybrid global optimization combines interval global optimization and nonlinear local optimization methods. The constraint propagation techniques are very effective in discarding infeas...

Multiobjective optimization problems (MOPs) have attracted intensive efforts from AI community and many multiobjective evolutionary algorithms (MOEAs) were proposed to tackle MOPs. In addition, a few researchers exploited MOEAs to solve constraint optimization problems (COPs). In this paper, we investigate how to tackle a MOP by iteratively solving a series of COPs and propose the algorithm nam...

Different constraint handling techniques have been used with multiobjective evolutionary algorithms (MOEA) to solve constrained multiobjective optimization problems. It is impossible for a single constraint handling technique to outperform all other constraint handling techniques always on every problem irrespective of the exhaustiveness of parameter tuning. To overcome this selection problem, ...

Historically, discrete minimization problems in constrained logical programming were modeled with the help of an isolated bounding constraint on the objective that is to be decreased. To overcome this frequently inefficient way of searching for improving solutions, the notion of optimization constraints was introduced. Optimization constraints can be viewed as global constraints that link the o...

Mobile robots that consist of a mobile platform with one or many manipulators mounted on it are of great interest in a number of applications. Combination of platform and manipulator causes robot operates in extended work space. The analysis of these systems includes kinematics redundancy that makes more complicated problem. However, it gives more feasibility to robotic systems because of the e...