The major function of dynamic networks is to sense information from the environment and process the information to the downstream. Therefore how to measure the information transmission ability of a dynamic network is an important topic to evaluate network performance. However, the dynamic behavior of a dynamic network is complex and, despite knowledge of network components, interactions and noi...

the markowitz’s optimization problem is considered as a standard quadratic programming problem that has exact mathematical solutions. considering real world limits and conditions, the portfolio optimization problem is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. therefore, the use of meta-heuristic methods such as neural networks and evolutionar...

This paper presents a decomposition approach for a quite general class of mixed-integer dynamic optimization problems that is capable of guaranteeing a global solution despite the nonconvexities inherent to the dynamic optimization subproblems. A case study is presented in connection to the optimal design and operation of a batch process consisting of a series reaction followed by a separation ...

In recent years, the vigorous rise in computational intelligence has opened up new research ideas for solving chemical dynamic optimization problems, making application of swarm-intelligence techniques more and widespread. However, potential algorithms with different performances still needs to be further investigated this context. On premise, paper puts forward a universal framework, which tra...

In this paper we consider the notion of rectangularity of a set of probability measures, introduced in Epstein and Schneider [4], from a somewhat different point of view. We define rectangularity as a property of dynamic decomposition of a distributionally robust stochastic optimization problem and show how it relates to the modern theory of coherent risk measures. Consequently we discuss robus...

The increasing penetration of renewable energy in recent years has led to more uncertainties in power systems. In order to maintain system reliability and security, electricity market operators need to keep certain reserves in the SecurityConstrained Economic Dispatch (SCED) problems. A new concept, deliverable generation ramping reserve, is proposed in this paper. The prices of generation ramp...

Particle swarm optimization (PSO) has shown to be a robust and efficient optimization algorithm therefore PSO has received increased attention in many research fields. This paper demonstrates the feasibility of applying the Dynamic Inertia Weight Particle Swarm Optimization to solve a Non-Polynomial (NP) Complete puzzle. This paper presents a new approach to solve the Nonograms Puzzle using Dyn...

This paper presents an investigation on the computational complexity of stochastic optimization problems. We discuss a scenariobased model which captures the important classes of two-stage stochastic combinatorial optimization, two-stage stochastic linear programming, and two-stage stochastic integer linear programming. This model can also be used to handle chance constraints, which are used in...

Dynamic lot sizing problem is one of the significant problem in industrial units and it has been considered by  many researchers. Considering the quantity discount in  purchasing cost is one of the important and practical assumptions in the field of inventory control models and it has been less focused in terms of stochastic version of dynamic lot sizing problem. In  this paper, stochastic dyn...

Based on the recent approach of Bertsimas and Sim (2004, 2003) to robust optimization in the presence of data uncertainty, we prove an easily computable and simple bound on the probability that the robust solution gives an objective function value worse than the robust objective function value, under the assumption that only cost coefficients are subject to uncertainty.We exploit the binary nat...