A common method to determine the order of minimal realization of a continuous linear time invariant descriptor system is to decompose it into slow and fast subsystems using the Weierstrass canonical form. The Weierstrass decomposition should be avoided because it is generally an ill-conditioned problem that requires many complex calculations especially for high-dimensional systems. The present ...

location-allocation is a combinatorial optimization problem, and is defined as non deterministic polynomial hard (np) hard optimization. therefore, solution of such a problem should be shifted from exact to heuristic or meta heuristic due to the complexity of the problem. locating medical centers and allocating injuries of an earthquake to them has high importance in earthquake disaster managem...

in this paper, a novel compensator based on magnetically controlled reactor with fixed capacitor banks (fc-mcr) is introduced and then power system stability in presence of this compensator is studied using an intelligent control method. the problem of robust fc-mcr-based damping controller design is formulated as a multi-objective optimization problem. the multi-objective problem is concocted ...

This paper discusses the use of optimization software to solve an optimal control problem arising in the modeling of technology transition. We set up a series of increasingly complex models with such features as learning-by-doing, adjustment cost, and capital investment. The models are written in continuous time and then discretized by using different methods to transform them into large-scale ...

The problem addressed is the optimization of the cyclic schedule of a mixed plant in order to maximize its productivity. A mixed plant is composed of batch and continuous tasks. A batch task has a fixed processing time and outputs at the end a fixed amount of product. A continuous task is processed continuously and its decision variable is the processing rate at which this continuous task is pe...

This paper focuses on the optimization of hyper-parameters for function approximators. We describe a kind of racing algorithm for continuous optimization problems that spends less time evaluating poor parameter settings and more time honing its estimates in the most promising regions of the parameter space. The algorithm is able to automatically optimize the parameters of a function approximato...

This paper presents how a problem of optimal trajectory planning, that is an optimal control problem, can be transformed into a parametric optimization problem and in consequence be tackled using efficient deterministic or stochastic parametric optimization techniques. The transformation is done thanks to discretizing some or all continuous system’s variables and forming their time-histories by...

  The traveling salesman problem is a well-known and important combinatorial optimization problem. The goal of this problem is to find the shortest Hamiltonian path that visits each city in a given list exactly once and then returns to the starting city. In this paper, for the first time, the shortest Hamiltonian path is achieved for 1071 Iranian cities. For solving this large-scale problem, tw...

Abstract. Time-varying network optimization problems have tradition-ally been solved by specialized algorithms. These algorithms have NP-complement time complexity. This paper considers the time-varying short-est path problem, in which can be optimally solved in O(T(m + n)) time,where T is a given integer. For this problem with arbitrary waiting times,we propose an approximation algorithm, whic...

Nonlinear Model Predictive Control (NMPC) has gained wide attention through the application of dynamic optimization. However, this approach is susceptible to computational delay, especially if the optimization problem cannot be solved within one sampling time. In this paper we propose an advanced-multi-step NMPC (amsNMPC) method based on nonlinear programming (NLP) and NLP sensitivity. This met...