Abstract
This paper studies the location-routing problem of big event logistics. We propose a mathematical model framework, which considers many aspects of logistics network design for big event, some of which have not received enough attention in the literature. Aspects to be considered include: multi-commodity, perishability of goods, combined storage strategy, vehicle capacity limitation, multi-vehicle, multi-point distribution, etc. In addition, while constructing the bi-objective model with the shortest total distribution time and the lowest total cost, the objective weight coefficients are set up according to the sensitivity of different perishable commodities to time and cost, and the sensitive types of each commodity are discussed. In terms of solving solution, the model is strengthened firstly, that is to reduce the number of 0–1 variables, increase the search space limitation, and do clustering analysis combined with the characteristics of data distribution. Finally, an optimized model is obtained, which is a mixed-integer linear programming model that can be tackled to get the optimal solution by an off-the-shelf solver using the branch and bound algorithm. In particular, we take the Beijing 2022 Winter Olympics as a practical case, and combine the location-routing results with the logistics situation in reality to discuss the impact of food perishability on the dual goals and give management inspiration through mathematical analysis.
Highlights
In this paper, we study the location-routing problem of multi-commodity and bi-objective
The above location results combined with routing strategy achieve the dual objectives of the lowest total distribution time and cost. Another innovation of this paper is that multi-commodity and perishability are considered simultaneously, and multi-vehicle distribution can not be mixed with different commodity types
By considering the commodity freshness penalty function, we constructed a mathematical model that meets the characteristics of Big event logistics (BEL) with the goal of minimizing time and cost
Summary
We study the location-routing problem of multi-commodity and bi-objective. P. Li et al.: Bi-Objective Capacitated Location-Routing Problem for Multiple Perishable Commodities. Due to the different demand for each kind of commodity at each demand point, it is necessary to allocate a reasonable proportion of multi-vehicle (different capacity limitation) to achieve the optimal combination of the type and quantity of goods loaded. BEL is a multi-objective combinatorial optimization problem about time and cost. Our main contribution is to find out the unique problems by discusssing the differences between BEL and other logistics, such as multi-demand points, multicommodities, multi-temperature control requirements (classified storage, classified transportation), multi-vehicle type, bi-objective, etc. How does the sensitivity of different types of perishable commodities to bi-objectives (time and cost) affect the location-routing results respectively?.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
