Multi-objective improved algorithm for flow allocations in hazardous chemicals logistics preference paths
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(3) 111-114
Jiaxing University, Jiaxing City, Zhejiang Province, China, 314200
The flow allocation of paths was a key stage of the transportation network’s efficiency, particularly in the hazardous chemicals logistics network where many weights were stochastic. Over the years, a variety of methods (or heuristics) have been proposed to solve this complex optimization problem, with good results in some cases just with limitations in the special fields. In this work, we develop an algorithm for model multi-objective that combines ideas from stochastic weight. Our method performs well even when the order of magnitude and/or the range of the parameters were unknown. The method refines iteratively a sequence of parameter distributions through preference combined with partial exampling from a historical prior defined over the support of all previous iterations. We exemplify our method with multi-objective improved models using both simulated and real experimental data and estimate the weight efficiently even in the absence of a priori knowledge about the weight.