Last-mile delivery is the last delivery step in the e-retail delivery process which delivered to the recipient, either of the recipient home or to the collection and delivery pick up points (CDPs). The objective of this research is to study on the last-mile delivery problem in terms of to avoid too many re-deliveries, by implementing convenience stores as delivery points in certain regions and areas in Jakarta City. This study also aims to examine the performances of collaboration among distribution systems with different chain convenience stores.
This research focuses on decreasing the failed first time delivery of e-commerce’s freight and proposes to implement two methods, clustering k-means, and traveling salesman problem, to analyze the study. Clustering k-means is used to group data that similar to the same cluster, and the traveling salesman problem is used to find the optimal route length. There will be the scenario on doing the traveling salesman problem which is collaboration and non-collaboration among the logistic service provider company. The results of this research show that collaboration among the logistics service provider has shorter travel distance than non-collaboration.

ACKNOWLEDGEMENTS ii
ABSTRACT iii
TABLE OF CONTENT iv
LIST OF TABLES vi
LIST OF FIGURES vii
Chapter 1 Introduction 1
1.1 Research Background and Motivation 1
1.2 Research Objectives 4
1.3 Research Contribution 4
1.4 Research Scope 5
1.4.1 Geography Scope 5
1.4.2 Research Procedure 5
Chapter 2 Literature Review 7
2.1 Last-Mile Delivery 7
2.2 Clustering K-means 10
2.3 Vehicle Routing Problem 13
2.3.1 Travelling Salesman Problem 13
2.3.2 Collaborative and Non-collaborative 14
Chapter 3 Methodology 16
3.1 Problem Statement 16
3.2 Model Assumption 18
3.2.1 Clustering K-Means 18
3.2.2 Travelling Salesman Problem 19
Chapter 4 Computational Result 21
4.1 Data Collection 21
4.2 Result 29
4.2.1 The First Clustering 29
4.2.1.1 Clustering K means 29
4.2.1.2 Travelling Salesman Problem (Shortest Path of first cluster) 35
4.2.1.2.1 Non-Collaboration Results 38
4.2.1.2.2 Collaboration Results 39
1.4.2 The Second Clustering 41
1.4.2.1 Clustering K-means 41
4.2.2.2 Travelling Salesman Problem (TSP) 45
4.2.2.2.1 Non-collaboration 45
4.2.2.2.2 Collaboration 48
Chapter 5 Conclusion and Suggestion 54
5.1 Conclusion 54
5.2 Managerial Implication 57
5.3 Research Limitation 57
5.4 Suggestion for Future Research 58
References 60

(2018). Retrieved from Aseanup: https://aseanup.com/top-e-commerce-sites-indonesia/
Agatz, N., Bouman, P., & Schmidt, M. (2018). Optimization Approaches for the Traveling Salesman Problem with Drone. Transportation Science.
Bouwman, M. (2017). Customer roles in the last-mile: Improving delivery performance.
City Distribution and Urban Freight Transport: Multiple Perspectives. (2011). In City Distribution and Urban Freight Transport: Multiple Perspectives (pp. 56-72). Edward Elgar.
Dailysocial.id. (2017 ). Retrieved from https://dailysocial.id/post/delivery-is-still-the-main-issue-for-indonesian-e-commerce
Ding, Z. (2013). Evaluating Different Last-mile Logistics Solutions. Faculty of engineering and sustainable development.
Feng, C.-M., & Huang, Y.-K. (2005). The choice behavior analysis on the pick-up point for the e-commerce retailing delivery . Journal of the Eastern Asia Society for Transportation Studies, 2778-2793.
Gupta, P., & Sethi, N. (2015). Comparative Study of Online and Offline Shopping: A case study of Rourkela in Odisha.
Kartal, Z., Hasgul, S., & Ernst, A. (2017). Single Allocation p-hub median location and routing problem with simultaneous pick-up and delivery. Transportation Research Part E, 141-159.
Lee, B., & Basri, M. H. (2017). Improvement on Delivery Service in Dropshipper Company: Case of Aquarist Farm. 3rd Parahyangan International Accounting & Business Conference 2017 (pp. 333-342). Bandung: piabc.fe.unpar.ac.id.
Li, Y., & Wu, H. (2012). A Clustering Method Based on K-Means Algorithm. Physics Procedia 25, 1104 – 1109.
Morganti, E., Seidel, S., Blanquart, C., Dablanc, L., & Lenz, B. (2014). The impact of e-commerce on final deliveries: alternative parcel delivery services in France and Germany. Transportation Research Procedia 4, 178-190.
Murray, C., & Chu, A. (2015). The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery. Transportation Research Part C, 86-109.
Nazeer, K., & M. P. Sebastian. (2009). Improving the Accuracy and Efficiency of the k-means Clustering Algorithm. Proceedings of the World Congress on Engineering.
Pan, S., Han, Y., Qiao, B., & Giannikas, V. (2016). Mining Customer-related Data to Enhance Home Delivery in E- commerce: an experimental study. 6th International Conference on Information Systems, Logistics and Supply Chain ILS Conference, 2016.
Pieri , S. P., Tzouvadakis, I., & Santamouris, M. (2015). Identifying energy consumption patterns in the Attica hotel sector using cluster analysis techniques with the aim of reducing hotels’ CO2 footprint. Energy and Building , 252-262.
Raval, U., & Jani, C. (2016). Implementing & Improvisation of K-mean Clustering Algorithm. International Journal of Computer Science and Mobile Computing, 191 – 203.
R, N. O., Innocent, O., & I.J, G. (2014). Modeling Of Travelling Salesman Routing Problems In Akwa Ibom State, Nigeria A Dynamic Programming Approach: Part 1. International Journal of Scientific & Engineering Research, 1997-2008.
Salman, R., Kecman, V., Li, Q., Strack, R., & Test, E. (2011). Fast K-Means Algorithm Clustering. International Journal of Computer Networks & Communications (IJCNC) , 17-31.
Shen, Y.-H. (June 2017). Discussion on Key Selection Criteria for Successful Management of Home Delivery. International Journal of Managerial Studies and Research (IJMSR), 63-71.
Van Duin, J., Goffau, W. d., Wiegmans, B., Tavasszy, L., & Saes, M. S. (2015). Improving home delivery efficiency by using principles of address intelligence for B2C deliveries. The 9th International Conference on City Logistics, Tenerife, Canary Islands (Spain), 14 – 25.
Veenstra, M., Roodbergen, K. J., Vis, I., & Coelho, L. (2017). The pickup and delivery travelling salesman problem with handling costs. European Journal of Operational Research, 118-132.
Villamizar, A. M., Torres, J. R., & Mejía, C. A. (2015). Non-Collaborative versus Collaborative Last-Mile Delivery in Urban Systems with Stochastic Demands. 7th Industrial Product-Service Systems Conference - PSS, industry transformation for sustainability and business (hal. 263-268). Universidad de La Sabana, km 7 autopista norte de Bogotá, D.C., Chía, Cundinamarca, Colombia: ScienceDirect.
Visser, J., Nemoto, T., & Browne, M. (2014). Home Delivery and The Impact on Urban Freight Transport: A Review. 8th International Conference on City Logistics , 15 – 27 .
Worldometers. (2018). Retrieved from Worldometers.info: http://www.worldometers.info/world-population/indonesia-population/