The tree tensor network (TTN) provides an essential theoretical framework for the practical simulation of quantum many-body systems, where structure defined by connectivity isometry tensors plays a crucial role in improving its approximation accuracy. In this paper, we propose TTN algorithm that enables us to automatically optimize local reconnections isometries suppress bipartite entanglement ...

1. Abstract Swarm algorithms such as Particle Swarm Optimization (PSO) are non-gradient probabilistic optimization algorithms that have been successfully applied to obtain global optimal solutions for complex problems such as multi-peak problems. However these algorithms have not been applied to complicated structural and mechanical optimization problems since local optimization capability is s...

A Reliability-Based Design Optimization (RBDO) framework is presented that accounts for stochastic variations in structural parameters and operating conditions. The reliability index calculation is itself an iterative process, potentially employing an optimization technique to find the shortest distance from the origin to the limit-state boundary in a standard normal space. Monte Carlo simulati...

This paper proposes an effective algorithm based on the level set method (LSM) to solve shape and topology optimization problems. Since the conventional LSM has several limitations, a binary level set method (BLSM) is used instead. In the BLSM, the level set function can only take 1 and -1 values at convergence. Thus, it is related to phase-field methods. We don’t need to solve the Hamilton-Jac...

This paper is devoted to the simultaneous weight and stiffness optimization of two dimensional structures. The necessary optimality conditions are derived and the obtained optimality criterion is briefly explained. Based on the paradigm of cellular automata, a local rule is constructed which alleviates the well known problems of mesh dependency and checker-boarding in topological structural opt...

Over the past few years, swarm intelligence based optimization techniques such as ant colony optimization and particle swarm optimization have received considerable attention from engineering researchers. These algorithms have been used in the solution of various structural optimization problems where the main goal is to minimize the weight of structures while satisfying all design requirements...

Opposition-based learning was first introduced as a solution for machine learning; however, it is being extended to other artificial intelligence and soft computing fields including meta-heuristic optimization. It not only utilizes an estimate of a solution but also enters its counter-part information into the search process. The present work applies such an approach to Colliding Bodies Optimiz...