in this paper the problem of minimizing the total transmitting power subject to a fixedtotal bit rate in ofdm systems is considered. upper bounds on transmitting power and bit rate ofeach subcarrier can also be taken into account. in practice, the number of bits of each subcarriershould be integer and nonnegative. in this paper an analytical optimal solution is derived for thecase of assuming t...

This study experimentally demonstrated a feed-forward inversion control scheme for maintaining an optimum incident irradiance on photobioreactors (PBRs) during batch cultivation. A data-based modelfree optimization using quadratic fit was utilized to rapidly estimate the optimum average fluence rate set point value that rendered maximum microalgae growth rate. Then, the feed-forward inversion c...

The reliability based design optimization (RBDO) method is prevailing in stochastic structural design optimization by assuming the amount of input data is sufficient enough to create accurate input statistical distribution. If the sufficient input data cannot be generated due to limitations in technical and/or facility resources, the possibility-based design optimization (PBDO) method can be us...

Purpose – The purpose of this paper is to propose a surrogate model-assisted optimization algorithm which effectively searches for the optimum at the earliest opportunity, avoiding the need for a large initial experimental design, which may be wasteful. Design/methodology/approach – The methodologies of two-stage and one-stage selection of points are combined for the first time. After creating ...

The simplex algorithm for linear programming is based on the fact that any local optimum with respect to the polyhedral neighborhood is also a global optimum. We show that a similar result carries over to submodular maximization. In particular, every local optimum of a constrained monotone submodular maximization problem yields a 1/2-approximation, and we also present an appropriate extension t...

in this paper, an integration of improve particle swarm optimization (ipso) incombination with successive quadratic programming (sqp) so called ipso-sqpalgorithm is proposed to solve time optimal bang-bang control problems. theprocedure is found not sensitive to the initial guess of the solution. due to randomselection in the first stage of the search process, the chance of converging to theglo...

this paper proposes the exchange market algorithm (ema) to solve the combined economic and emission dispatch (ceed) problems in thermal power plants. the ema is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. existence of two seeking operators in ema provides a high ability in exploiting global optimum point. in order to show the capabilities ...

To maximize the downlink code-division multiple access (CDMA) system capacity, we propose to minimize the total transmitted power of the system subject to users’ signal-to-interference ratio (SIR) requirements via designing optimum transmitter sequences and utilizing linear optimum receivers (minimummean square error (MMSE) receiver). In our work on joint transmitter-receiver design for the dow...

Particle swarm and simulated annealing optimization algorithms proved to be valid in finding a global optimum in the bound constrained optimization context. However, their original versions can only detect one global optimum even if the problem has more than one solution. In this paper we propose modifications to both algorithms. In the particle swarm optimization algorithm we introduce gradien...

Abstract: Engineering optimization problems are normally formulated as nonlinear programming problems and adopted in a lot of research to show the effectiveness of new optimization algorithms. These problems are usually solved through deterministic or heuristic methods. Because non-convex functions exist in most engineering optimization problems that possess multiple local optima, the heuristic...