Integration of Information and Optimization Models for Routing in City Logistics

Online-Ressource (XIV, 197p. 76 illus., 17 illus. in color, digital)

International Series in Operations Research & Management Science ; 177

Description based upon print version of record

Integration of Information and Optimization Models for Routing in City Logistics; Foreword; Contents; Abbreviations; Symbols; 1 Introduction; Part I Problem Description; 2 City Logistics; 2.1…Challenges; 2.1.1 Evolution of Supply ChainsSupply Chain'' \b; 2.1.2 Increasing (Freight) Traffic; 2.2…Solution Concepts; 2.2.1 Perspective of Different Stakeholders; 2.2.2 Urban Consolidation CentersUrban consolidaten center, UCC'' \b; 2.2.3 City LogisticsCity logistics Initiatives; 2.3…Modeling; 2.4…Planning SystemsPlanning system'' \b; 2.4.1 Levels of PlanningPlanning

2.4.2 Architecture of a Planning SystemPlanning system3 Attended Home Delivery; 3.1…Online Retail; 3.2…Types of Last-Mile Delivery; 3.3…Customer Time Windows; 3.3.1 Tactical Planning; 3.3.2 Operational Planning; 3.4…Implications; Part II Information Models; 4 Knowledge Discovery and Data Mining; 4.1…Knowledge Discovery Process Knowledge Discovery Process, KDD; 4.1.1 Preprocessing; 4.1.1.1 Data CleaningPreprocessingData Cleaning'' \bData Cleaning'' \b; 4.1.1.2 Data IntegrationPreprocessingData IntegrationData Integration; 4.1.2 Data Mining Data Mining, DM'' \b; 4.1.3 Verification

4.2…Cluster AnalysisCluster analysis'' \t ''See Clustering4.2.1 Clustering Approaches; 4.2.2 Clustering AlgorithmsClusteringCluster algorithm; 4.2.2.1 k-Means Clusteringk-Means'' \b; 4.2.2.2 k-Medoids Clusteringk-Medoids'' \b; 4.2.2.3 DBSCANClusteringDBSCAN'' \b; 4.2.3 Validation of Clusterings; 4.2.3.1 Clustering Tendency (Hopkin's Statistics) Cluster validationClustering tendency Clustering tendency Cluster validationHopkin's statistics Hopkin's statistics'' \b; 4.2.3.2 Davies-Bouldin IndexCluster validationDavies-Bouldin index, DBI Davies-Bouldin index, DBI

4.2.3.3 Suitable Number of Clusters (Elbow Criterion) Cluster validationNumber of clusters4.3…Exploratory Data AnalysisExploratory Data Analysis, EDA'' \bData Mining, DMExploratory Data Analysis, EDA'' \b; 5 Analysis of Floating Car Data; 5.1…Data CollectionData collection; 5.1.1 Traditional Approach; 5.1.2 TelematicsTelematics-Based Approach; 5.1.2.1 Data CollectionData collection by FCD; 5.1.2.2 Data CollectionData collection by Taxi-FCDTaxi-FCD; 5.2…Preprocessing; 5.2.1 Attribute ''Time''; 5.2.2 Attribute ''Link''Link; 5.2.3 Attribute ''Speed''; 5.2.4 Temporal Distribution of Measurements

5.2.5 Spatial Distribution of Measurements5.3…First Level AggregationFirst level aggregation; 5.4…Second Level AggregationSecond level aggregation; 5.4.1 Preprocessing; 5.4.2 Clustering TendencyCluster validationClustering tendencyClustering tendency; 5.4.3 Clustering Approach; 5.4.4 Number of ClustersCluster validationNumber of clusters; 5.5…Exploratory Data AnalysisExploratory Data Analysis, EDAData Mining, DMExploratory Data Analysis, EDA; 5.5.1 First Level AggregationFirst level aggregation; 5.5.2 Second Level Aggregation Second level aggregation

Part III Integration of Information Models

10.1007/978-1-4614-3628-7 [DOI]

ECONIS - Online Catalogue of the ZBW