Vehicle Routing under Consideration of Driving and Working Hours - A Distributed Decision Making Perspective

Foreword

Preface

Contents

List of Figures

List of Tables

Abbreviations

1 Introduction

1.1 Problem Description

1.2 Related Literature

1.3 Objectives and Structure of the Thesis

2 European Legislation on Driving and Working Hours in Road Transportation

2.1 Regulation (EC) No 561/2006 on Driving Hours

2.1.1 Scope

2.1.2 Definitions

2.1.3 Restrictions on Driving Hours

2.1.4 Documentation of Driving Times

2.1.5 Comparison Between Current and Former European Legislation on Driving Hours

2.2 Directive 2002/15/EC on Working Hours

2.2.1 Scope

2.2.2 Definitions

2.2.3 Restrictions on Working Hours

2.2.4 Implementation into German Legislation

2.3 Remarks on the General Structure of the European Social Legislation

2.4 Control Policies

3 Dispatchers’ Tasks in Combined Vehicle Routing and Break Scheduling

3.1 The Dispatching Process

3.2 The Impact of the European Social Legislation on the Dispatching Process

3.2.1 Effects on Vehicle Routing and Scheduling

3.2.2 Examples of Effects

3.3 Combined Vehicle Routing and Break Scheduling in Practice

3.3.1 Methodology of the Study

3.3.2 Interviews with Freight Forwarding Companies

3.3.3 Summary of the Findings

4 Model for the Vehicle Routing Problem with Time Windows and European Social Legislation

4.1 Model for the VRPTW-EU with Basic Rules

4.1.1 Problem Definition

4.1.2 Notation

4.1.3 Model Formulation

4.2 Model for the VRPTW-EU with Optional Rules

4.2.1 Problem Definition

4.2.2 Notation

4.2.3 Model Formulation

4.3 Computional Experiments

4.3.1 Experimental Settings

4.3.2 Computational Results for the VRPTW-EU

4.3.3 Example of a Tour Plan

5 Distributed Decision Making in Combined Vehicle Routing and Break Scheduling

5.1 The Distributed Decision Making Framework

5.1.1 Classification of Distributed Decision Making Systems

5.1.2 Coordination in Distributed Decision Systems

5.2 The Problem of Combined Vehicle Routing and Break Scheduling as a Problem of Distributed Decision Making

5.2.1 Distribution of Tasks between Planners and Drivers

5.2.2 Anticipation of the Drivers’ Planning

5.3 Model Formulations

5.3.1 Driver’s Model

5.3.2 Dispatcher’s Model

5.3.3 Anticipation Functions

5.3.3.1 Perfect Explicit Anticipation

5.3.3.2 Approximate Explicit Anticipation

5.3.3.3 Implicit Anticipation

5.4 Computational Experiments for the Decentralized Approaches

5.4.1 Experimental Settings and Solution Procedure

5.4.2 Computational Results

5.4.2.1 Perfect Explicit Anticipation

5.4.2.2 Approximate Explicit Anticipation

5.4.2.3 Implicit Anticipation

5.4.3 Summary of the Findings

6 Restricted Dynamic Programming Heuristic for the Problem of Combined Vehicle Routing and Break Scheduling

6.1 Dynamic Programming Methods for Vehicle Routing Problems

6.1.1 Dynamic Programming Algorithm for the Traveling Salesman Problem

6.1.2 Restricted Dynamic Programming Algorithm for the Traveling Salesman Problem

6.1.3 Solving Vehicle Routing Problems via Giant-Tour Representations

6.2 Restricted Dynamic Programming Heuristic for the Vehicle Routing Problem with Time Windows and European Social Legislation

6.2.1 Basic Break Scheduling Method

6.2.2 Extended Break Scheduling Method

6.2.2.1 Extended Daily Driving Times

6.2.2.2 Reduced Daily Rest Periods

6.2.2.3 Split Breaks

6.2.2.4 Split Daily Rest Periods

6.2.2.5 Overview of the Implementations of the Optional Rules

6.2.3 Extensions to Different Time Horizons

6.2.4 Computational Experiments

6.3 Distributed Decision Making Using the Restricted Dynamic Programming Heuristic

6.3.1 Computational Experiments for the Decentralized Planning Approach

6.3.1.1 Team Situation

6.3.1.2 Non-Team Situation

6.3.2 Summary of the Findings

7 Conclusions and Further Research

7.1 Conclusions for Vehicle Routing Under Consideration of Driving and Working Hours

7.2 Outline of Further Research Directions

Bibliography