Desain Antarmuka Pada Vehicle Routing Problem Untuk Manajemen Armada Multi-Drone
Article Sidebar
Main Article Content
Abstract
Artikel ini membahas desain antarmuka pada vehicle routing problem (VRP) 3-dimensi untuk armada multi-drone. Armada ini melakukan perjalanan untuk mengunjungi serangkaian titik dengan memperhatikan batasan tertentu. Karena VRP diklasifikasikan sebagai masalah optimasi NP-hard, algoritma aproksimasi seperti Algoritma Genetika diterapkan untuk menemukan solusi terbaik untuk masalah optimisasi kombinatorial ini. Dalam merancang GUI ini, kami menggunakan Netlogo sebagai alat untuk membangun antarmuka, dan juga untuk eksperimen dan simulasi. Hasil penelitian ini menunjukkan bahwa dengan menggunakan Netlogo, kita dapat mendesain antarmuka untuk mensimulasikan algoritma aproksimasi dalam penyelesaian permasalahan optimasi kombinatorial, yang mudah dioperasikan oleh pengguna
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work’s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
[2] Laporte, G., 1992, The Vehicle Routing Problem: An overview of exact and approximate algorithms, European Journal of Operational Research, Vol. 59, pp. 345-358.
[3] Dantzig, G. B. and Ramser, J. H., 1959, The Truck Dispatching Problem, Management Science, INFORMS, Vol. 6, No. 1, pp. 80-91.
[4] Karakatic, K. and Podgorelec, V., 2015, A survey of genetic algorithms for solving multi depot vehicle routing problem, Applied Soft Computing, 27, 519–532.
[5] Goldberg, D.E., 1989, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, New York.
[6] Tisue, S. and Wilensky, U., 2004, Netlogo: A Simple Environment for Modelling Complexity, International Conference on Complex Systems (ICCS), Boston, May 16 - 21.
[7] Netlogo Home Page. [Online]. Tersedia di : https://ccl.northwestern.edu/netlogo/references.shtml. [Diakses pada Januari 2018]
[8] Sukarno, S.A., Atitallah, R.B. and Djemai, M., 2018, Approximation Algorithm for 3-Dimensional Vehicle Routing Problem for Fleet of Multi-Agents. 2018 6th International Conference on Control Engineering & Information Technology (CEIT), Istanbul, Turkey, pp. 1-6. doi: https://doi.org/10.1109/CEIT.2018.8751928
[9] Umbarkar, A.J. and Sheth, P.D., 2015, Crossover Operators in Genetic Algorithms: A Review, ICTACT Journal on Soft Computing, Vol. 06, Issue: 01.
[10] Hileman, W., Netlogo User Community Models, Classic Travelling Salesman. [Online]. Tersedia di: http://ccl.northwestern.edu/netlogo/models/community. [Diakses pada Januari 2018]
[11] Sukarno, S.A., 2019. Approximation Methods to Vehicle Routing Problem for a Drone Fleet Management. Ph.D. Valenciennes, France: Université Polytechnique Hauts de France.