Abstract
We consider a rich tanker trailer routing problem with stochastic transit times for chemicals and liquid bulk orders. A typical route of the tanker trailer comprises of sourcing a cleaned and prepped trailer from a pre-wash location, pickup and delivery of chemical orders, cleaning the tanker trailer at a post-wash location after order delivery and prepping for the next order. Unlike traditional vehicle routing problems, the chemical interaction properties of these orders must be accounted for to prevent risk of contamination which could impose complex product-sequencing constraints. For each chemical order, we maintain a list of restricted and approved prior orders, and a route is considered to be feasible if it complies with the prior order compatibility relationships. We present a parallel computation framework that envelops column generation technique for large-scale route evaluations to determine the optimal trailer-order-wash combinations while meeting the chemical compatibility constraints. We perform several experiments to demonstrate the efficacy of our proposed method. Experimental results show that the proposed parallel computation yields a significant improvement in the run time performance. Additionally, we perform sensitivity analysis to show the impact of wash capacity on order coverage.
Highlights
According to American Chemical Council (ACC), the chemical industry accounts for a $797B enterprise that is projected to increase its capacity by 18% in 2020, resulting in complexity in transportation (Baldwin 2017)
We analyze a rich tanker trailer routing problem with stochastic travel times for chemical orders where the chemical interaction properties of the orders create an additional complexity while determining the best strategies to dispatch trailers
To address large-scale nature of the problem, we propose an integrated approach which incorporates the efficacy of stochastic models, column generation technique and parallel computation to generate the optimal candidate routes
Summary
According to American Chemical Council (ACC), the chemical industry accounts for a $797B enterprise that is projected to increase its capacity by 18% in 2020, resulting in complexity in transportation (Baldwin 2017). Unlike classical transportation problems (Dantzig and Ramser 1959), chemical transportation involves two additional constraints: hazardous interaction properties among chemicals, and washing decisions (e.g., location, wash type) for trailers after delivery. These constraints need to be addressed in addition to those involved. “Mathematical model” section presents the mathematical model formulation of the proposed method Using these specialized set of mathematical models, we develop an exact solution methodology to solve complex tanker trailer routing problems with stochastic transit times. “Numerical experiments” section summarizes numerical experiments conducted for the proposed system It includes the details of sensitivity analysis performed to analyze the impact of several factors on the performance of the model.
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