Research On Bidding Generation For Transportation Service Procurement Considering Selective Requests

Transportation services are an important part of logistics operations in modern logistics systems,and have a significant impact on a company’s operational efficiency and cost control.To meet the needs of logistics operations,companies typically outsource transportation services to logistics providers,a process known as transportation service procurement,which is an essential part of a company’s logistics operations.Transportation service procurement involves two roles: the shipper and the carrier.The shipper needs to select the appropriate transportation mode,time,and cost based on their own transportation needs in order to choose the most suitable supplier.The carrier needs to provide efficient,stable,and reliable transportation services to meet the needs of their customers.In transportation service procurement,there needs to be sufficient communication and cooperation between the shipper and the carrier to ensure the smooth operation of transportation services.In this process,the shipper holds an auction to obtain transportation services,and the carrier participates as a bidder to obtain greater profits.At this point,bid generation becomes an important issue.The carrier needs to make two important decisions during the bidding process: selecting the appropriate bid combination and planning the route after bidding.To solve this problem,this thesis establishes a bid generation problem model based on the carrier’s perspective,with the carrier’s maximum profit as the objective function,satisfying constraints such as transportation time windows,maximum transportation distance,and vehicle load,to help the carrier select the optimal combination and plan the route reasonably.Considering that the bid generation problem is an NP-hard problem,this thesis designs a two-stage particle swarm algorithm to solve the bid generation problem.Specifically,the bid generation problem is divided into two stages: bid combination and pricing,and route planning after combination.In the bid generation stage,the carrier needs to select suitable transportation tasks,routes,and synergies based on their own transportation network and resource situation,and find the optimal bid combination through synergy calculation and pricing.In the route planning stage,the auction algorithm is used to allocate the carrier’s selected bids to existing transportation routes,and the particle swarm algorithm is used to plan the new route.This thesis analyzes two numerical examples to verify the effectiveness of the algorithm.The experimental results show that this approach can effectively solve the bid generation problem and increase the carrier’s profit.In addition,this thesis also conducts sensitivity analysis on factors that affect the carrier’s profit.In modern logistics operations,transportation service procurement is an essential part,and the bid generation problem model and algorithm proposed in this thesis can provide companies with more efficient,stable,and reliable transportation services,which is of great significance for improving a company’s operational efficiency and cost control.