The paper introduces a complete offline programming toolbox for remote laser welding (RLW) which provides a semi-automated method for computing close-to-optimal robot programs. A workflow is proposed for the complete planning process, and new models and algorithms are presented for solving the optimization problems related to each step of the workflow: the sequencing of the welding tasks, path ...

Numerous items, small order, and frequent delivery are the characteristics of many distribution centers. Such characteristics generally increase the operating costs of the distribution center. To remedy this problem, this study employs the Entry-Item-Quantity EIQ method to identify the characteristic of the cigarette distribution center and further analyzes the importance degree of customers an...

A new matroid is introduced: this matroid is de0ned starting from any matroid and one of its bases, hence we call it base-matroid. Besides some properties of the base-matroid, a non-trivial algorithm for the solution of the related matroid optimization problem is presented. The new matroid has application in the 0eld of inverse combinatorial optimization problems. We discuss in detail the LP fo...

We present a novel GPU-accelerated per-pixel inverse rendering optimization algorithm based on Particle Swarm Optimization (PSO). Our algorithm estimates the per-pixel scene attributes—including reflectance properties—of a 3D model, and is fast enough to do in situ visualization of the optimization in real-time. The algorithm’s high parallel efficiency is demonstrated through our GPU/GLSL shade...

The gradient geometry-optimization procedure is reformulated in terms of redundant internal coordinates. By replacing the matrix inverse with the generalized inverse, the usual NewtonRaphson-type algorithms can be formulated in exactly the same way for redundant and nonredundant coordinates. Optimization in redundant coordinates is particularly useful for bridged polycyclic compounds and cage s...

Given the costs and a feasible solution for a linear program, inverse optimization involves finding new costs that are close to the original ones and make the given solution optimal. We develop an inverse optimization framework for countably infinite linear programs using the weighted absolute sum metric. We reformulate this as an infinite-dimensional mathematical program using duality. We prop...