For most practical purposes, true topology optimization of a braced frame should be synchronized with its sizing. An integrated layout optimization is formulated here to simultaneously account for both member sizing and bracings’ topology in such a problem. Code-specific seismic design spectrum is applied to unify the earthquake excitation. The problem is solved for minimal structural weight un...

Particle swarm optimization (PSO) is a kind of evolutionary algorithm to find optimal solutions for continuous optimization problems. Updating kinetic equations for particle swarm optimization algorithm are improved to solve traveling salesman problem (TSP) based on problem characteristics and discrete variable. Those strategies which are named heuristic factor, reversion mutant and adaptive no...

A new meta-heuristic algorithm is proposed for optimal design of reinforced concrete (RC) frame structures subject to combinations of gravity and lateral static loads based on ACI 318-08 design code. In the present work, artificial bee colony algorithm (ABCA) is focused and an improved ABCA (IABCA) is proposed to achieve the optimization task. The total cost of the RC frames is minimized during...

Optimization problems attempt to find out the minimum or maximum of a certain function (usually referred to as the cost function). The cost function can either be continuous or discrete. Discrete optimization problems arise, when the variables occurring in the optimization function can take only a finite number of discrete values and also subject to constraint conditions. In continuous optimiza...

This paper investigates a discrete-time impatient customer queue with Bernoulli-schedule vacation interruption. The  vacation times and the service times during regular busy period and during working vacation period are assumed to follow geometric distribution. We obtain the steady-state probabilities at arbitrary and outside observer's observation epochs using recursive technique. Cost analysi...

Trajectory optimization involves both the optimization of inputs and the feedback regulation of the resulting trajectories. This article covers the main points of adapting trajectory optimization to the numerical routines in discrete mechanics. We start with a brief description of discrete mechanics and variational integrators and then move on to linearization, estimation, local projections in ...

We formulate the sparse classification problem of n samples with p features as a binary convex optimization and propose outer-approximation algorithm to solve it exactly. For logistic regression SVM, our finds optimal solutions for in 10,000 s within minutes. On synthetic data achieves perfect support recovery large sample regime. Namely, there exists an $$n_0$$ such that takes long time find s...