In response to the challenge by Ramchurn et al. to solve smart grid optimization problems with artificial intelligence techniques [21, 23], we investigate the feasibility of solving two common smart grid optimization problems as distributed constraint optimization problems (DCOPs). Specifically, we look at two common customer-driven microgrid (CDMG) optimization problems – a comprehensive CDMG ...

Constraint programming (CP) offers flexible and effective tools for modeling combinatorial optimization problems. At the same time, scheduling with sum type optimization criteria, such as total completion time is challenging for CP. In this paper we show how extending a standard CP solver by a global constraint on total completion time can boost the performance of CP on various, seemingly very ...

We describe strong convex valid inequalities for conic quadratic mixed 0-1 optimization. The inequalities exploit the submodularity of the binary restrictions and are based on the polymatroid inequalities over binaries for the diagonal case. We prove that the convex inequalities completely describe the convex hull of a single conic quadratic constraint as well as the rotated cone constraint ove...

This paper presents a new observer design methodology for a time varying actuator fault estimation. A new linear matrix inequality (LMI) design algorithm is developed to tackle the limitations (e.g. equality constraint and robustness problems) of the well known so called fast adaptive fault estimation observer (FAFE). The FAFE is capable of estimating a wide range of time-varying actuator fault...

This paper applies an evolutionary algorithm, the particle swarm optimization (PSO), to design the optimum open channel section. Depth, channel side slope and bottom width are considered as the variables for rectangular, triangular and trapezoidal channels, respectively. The objective function is minimizing the construction cost of the channel section. MATLAB software is used for programming an...

An algorithm for the constant time solution of systems of geometric constraint equations is presented in this work Constraint equations and their Jacobians may be used in conjunction with other numerical methods to solve for a variety of kinematics dynamics and assembly optimization problems The use of constraint equations for these purpose is an under utilized method in this area The use of qu...

In this paper we discuss how the ability of the constraint solvers to deal with constraint minimization can be lifted up to various forms of goal optimization within CLP languages. We emphasis the link there is between optimization and negation both in the declarative semantics and in the operational aspects. We also discuss the design of incremental execution models in an \optimization as inte...

In this paper, an efficient method for solving optimal control problems of the linear differential systems with inequality constraint is proposed. By using new adjustment of hat basis functions and their operational matrices of integration, optimal control problem is reduced to an optimization problem. Also, the error analysis of the proposed method is nvestigated and it is proved that the orde...

In this paper, we study the problem of minimizing the ratio of two quadratic functions subject to a quadratic constraint. First we introduce a parametric equivalent of the problem. Then a bisection and a generalized Newton-based method algorithms are presented to solve it. In order to solve the quadratically constrained quadratic minimization problem within both algorithms, a semidefinite optim...

A framework which applies distributed constraint optimization method using depth first search tree to dynamic problem is proposed. The proposed framework is considered as a basic model of multi agent system. The agents communicate with each other to solve the problem. Constraint network for the problem is built. Trees, which are similar to depth first search tree for the constraint network, are...