Optimization of Transportation Routing Problem for Fresh Food by Improved Ant Colony Algorithm Based on Tabu Search

Chen Chen,Na Na,Ding Ding,Zhou Zhou,Gui Gui

doi:10.3390/su11236584

Abstract

With the continuous improvement of people’s living standards and their increasing demand for fresh food, the cold chain logistics industry has developed rapidly. One of the biggest challenges to today’s cold chain logistics is to offer fresh food while minimizing CO2 emissions. The fresh degree and CO2 emissions are involved in the vehicle routing optimization problem in the cold chain logistics. In order to meet the quality requirement for fresh agricultural products and low carbon logistics, a novel routing optimization model considering the costs of quality deterioration and carbon emissions (Low Carbon and Freshness Degrees Vehicle Routing Problem (LCFD-VRP)) for cold chain distribution was established in this study. This model takes into account the fixed cost, fuel cost and time window penalty cost. An improved ant colony algorithm (IACA) is used to optimize the whole vehicle distribution routing with its strong global search ability. Tabu Search (TS) algorithm is used to search the single vehicle distribution routing with its good local search ability. An IACA combined with TS (IACATS) was proposed to solve the above LCFD-VRP model. The practicability of the model and the effectiveness of the above improved algorithm are verified using a real case study. The results of Zhoushan Dayang Refrigerated Logistics Co., Ltd. showed that, compared with the traditional algorithm, IACATS could reduce the dispatching of two refrigerated vehicles, thus lowering the total cost by 4.94%, shortening the actual transportation distance by 5.50% and cutting the total CO2 emissions by 8.9%. Therefore, the LCFD-VRP model can effectively help to achieve the low carbon emissions, multi-variety and low-cost distribution of fresh agricultural products. The proposed model and IACATS algorithm would be used to optimize VRP in cold chain enterprises. The results of this study also provide management suggestions for cold chain enterprises to effectively balance economic cost and environmental cost.

Highlights

With the development of the economy and the improvement in people’s life quality, green and healthy products have gradually become the primary standard for consumers to choose fresh foods [1]
Our results demonstrate that IACA combined with TS (IACATS) could reduce the dispatching of two refrigerated vehicles, lowering the total cost by 4.94%, shortening the real transportation distance by 5.50% and cutting the total CO2 emissions by 8.9% compared with the traditional ant algorithm mode
The optimization of cold chain logistics routing problem was studies while we considered carbon emissions and product freshness

Summary

Introduction

With the development of the economy and the improvement in people’s life quality, green and healthy products have gradually become the primary standard for consumers to choose fresh foods [1] This has resulted in the rapid development of global fresh agricultural products via cold chain logistics around the world. The normal operation of refrigeration equipment produces a large amount of CO2 emissions and other greenhouse gases generated from distribution vehicles in the process of delivery. It leads to an increase in greenhouse gases and, as a result, air pollution and greenhouse effect will be intensified. How to reduce carbon emissions in cold chain logistics, thereby alleviating the global warming caused by the greenhouse effect, has become a popular issue in the research field of cold chain logistics distribution routes [4]

Results

Discussion

Conclusion