Abstract

Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD) has been studied for long years and used to model for many real-life applications. The problem is basically to find optimal routes for vehicles that serve customers in a service area to collect as well as deliver goods at the same time. Many logistic companies such as cargo, post, online supermarket, etc. face this problem in their daily operations. Because of high competitions in the sector, companies start to provide visit time preferences that customers can select. Although this is highly preferred by customers, it causes additional costs for companies since it is highly probable that preferences of customers violate optimal routes of vehicles. This problem is called as VRPSPD in Time Windows (VRPSPDTW). In this study, we develop a tactical/strategic level pricing policy based on calculation of additional travel time cost caused by visit time preferences of customers. Idea behind the policy is that solving VRPSPD for same customer set with/without considering time windows in each trial. After conducting many trials for different customer sets, average differences between travel times of VRPSPD and VRPSPDTW are determined. A generic hourly additional prices based on the average differences are calculated. Both problems are modelled as mixed ineger linear programmings and solved with CPLEX 12.9. Differences among travel times vary from 32 to 180 minutes according to experimental settings. Furthermore, results do not only change with time windows, but also different service regions play important role on results.

Highlights

  • Vehicle Routing Problem (VRP) has been studied since the study of Dantzig and Ramser [1], “The Truck Dispatching Problem”, 1959

  • The mixed integer linear programming is coded with AMPL (A mathematical programming language) IDE 3.5 software and solved with CPLEX 12.9

  • A new methodology is proposed to determine a tactical or strategic pricing policy for companies that deal with VRPSPD and time windows (VRPSPDTW)

Read more

Summary

Introduction

Vehicle Routing Problem (VRP) has been studied since the study of Dantzig and Ramser [1], “The Truck Dispatching Problem”, 1959. The problem was to find optimal routes for vehicles that deliver gasoline from a bulk terminal to many gasoline stations. Many different extensions such as multidepot, capacity, time windows, stochastic service and travel times as well as solution methods such as the linear programming, mixed integer programming, saving heuristics, tabu search, genetic algorithm have been proposed since [2]. Orders are distributed to customers while same vehicles pick up undated goods or empty bottles. Another sector as an example for VRPSPD is the reverse logistics. Some companies are responsible products during their whole life cycles (as in the disposal of laser printers’ cartridges) [4]

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

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 call