Showing papers by "Jun Zhang published in 2016"
TL;DR: Experimental results showed that the MLACO approach was able to match solution qualities and reduce computing time significantly compared to the tested approaches.
Abstract: This paper presents a multilevel ant colony optimization (MLACO) approach to solve constrained forest transportation planning problems (CFTPPs). A graph coarsening technique is used to coarsen a network representing the problem into a set of increasingly coarser level problems. Then, a customized ant colony optimization (ACO) algorithm is designed to solve the CFTPP from coarser to finer level problems. The parameters of the ACO algorithm are automatically configured by evaluating a parameter combination domain through each level of the problem. The solution obtained by the ACO for the coarser level problems is projected into finer level problem components, which are used to help the ACO search for finer level solutions. The MLACO was tested on 20 CFTPPs and solutions were compared to those obtained from other approaches including a mixed integer programming (MIP) solver, a parameter iterative local search (ParamILS) method, and an exhaustive ACO parameter search method. Experimental results showed that the MLACO approach was able to match solution qualities and reduce computing time significantly compared to the tested approaches.
12 citations
TL;DR: A higher order alternating direction implicit (ADI) method with completed Richardson extrapolation with high accuracy for solving unsteady two dimensional convection-diffusion equations and stability analysis is given.
Abstract: A higher order alternating direction implicit (ADI) method with completed Richardson extrapolation is proposed for solving unsteady two dimensional convection-diffusion equations. The method has sixth-order accuracy in space and fourth-order accuracy in time. Completed Richardson extrapolation is used to improve the accuracy of the solution obtained from the high-order ADI method in spatial and temporal domains simultaneously. Stability analysis is given to show the influence of Richardson extrapolation on the unconditionally stable ADI method. Numerical experiments are conducted to test its high accuracy and to compare it with Karaa-Zhang's high-order ADI method.
7 citations