Abstract

Using new optimization methods and information-communications technology has become the key issue in the competition among the distributers of fast-moving consumer goods. Introducing a delivery optimization system instead of manual routing enables significant cost savings. The prerequisites for optimization are stable information system and efficient company management. The rich vehicle routing problem model is discussed and the effects of implementing the delivery optimization system are presented. For four years of continuous utilisation, the system has helped the distributer to reduce the overall distribution costs. It also made possible to close down several depots and handle more customer requests without investing in the vehicle fleet. The developed optimization system enabled the distributer to adapt to the new distribution schedule and react to first indicators of recession very fast.

Highlights

  • During the last decade, the competition among the Croatian distributers of fast-moving consumer goods in the commercial logistics sector has increased

  • This paper presents the effects of implementing a delivery optimization system in case of a distributer of fast-moving consumer goods

  • The presented case study of a distributer of fastmoving consumer goods could be modelled like a mix fleet multi depot Vehicle Routing Problem with Time Windows (VRPTW) with multi-commodity

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Summary

INTRODUCTION

The competition among the Croatian distributers of fast-moving consumer goods in the commercial logistics sector has increased. New technologies such as delivery optimization and fleet management software emerged as the key advantage in competition of distributers. Transportation costs can be reduced significantly if manual delivery planning process is entirely replaced or augmented by some kind of optimization software. This paper presents the effects of implementing a delivery optimization system in case of a distributer of fast-moving consumer goods.

PROBLEM DESCRIPTION AND MODELLING ISSUES
Standard VRP models
The Rich-VRP
Case study modelling issues
OPTIMIZATION PROCESS
Manual and automatic routing
Solvers and algorithms
EXTENSION TO 2-ECHELON VRP
NEW OPTIMIZATION SCENARIO
Findings
CONCLUSION
Full Text
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