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Journal : Jurnal Kajian Matematika dan Aplikasinya

TWO PHASE HEURISTIC ALGORITHM (TPHA) PADA MULTIPLE TRAVELLING SALESMAN PROBLEM (MTSP) DAN IMPLEMENTASI PROGRAMNYA Rahma Try Iriani; Sapti Wahyuningsih; Darmawan Satyananda
Jurnal Kajian Matematika dan Aplikasinya (JKMA) Vol 1, No 1 (2020): July
Publisher : UNIVERSITAS NEGERI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um055v1i12020p10-17

Abstract

Multiple Traveling Salesman Problem (MTSP) is one variant of Traveling Salesman Problem (TSP) which involves several salesmen in making a trip to visit several customers. In this article, the Two-Phase Heuristic Algorithm (TPHA) is used to solve MTSP problems. The algorithm classifies customers into several regions using the K-Means algorithm, which will then find a route solution for each region using a genetic algorithm. The MTSP problems that were resolved using TPHA were implemented into the Borland Delphi 7.0 programming language. Application testing was conducted using 21, 32, and 46 point cases.
ALGORITMA GENERAL VARIABLE NEIGHBORHOOD SEARCH PADA CAPACITATED VEHICLE ROUTING PROBLEM WITH TIME WINDOWS DAN IMPLEMENTASINYA Ulil Ilmi Fadila; Sapti Wahyuningsih; Darmawan Satyananda
Jurnal Kajian Matematika dan Aplikasinya (JKMA) Vol 3, No 1 (2022): January
Publisher : UNIVERSITAS NEGERI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um055v3i12022p1-7

Abstract

The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is one of the variants of the Vehicle Routing Problem (VRP), which is the problem of determining the optimal route from the depot to the consumer which is located spread out with different requests. In CVRPTW problem solving considers capacity and time constraints. Determining the optimal route can reduce costs and energy spent during the distribution process. The General Variable Neighborhood Search (GVNS) algorithm can be applied to the CVRPTW problem. The GVNS algorithm is an improvement on the VNS algorithm using RVND. The GVNS algorithm starts with finding the initial solution, continues with perturbation, and then the repair procedure is carried out. Perturbation and improvements to the GVNS algorithm are performed repeatedly according to the predetermined IterMax. The GVNS algorithm for CVRPTW will be implemented using the Borland Delphi 7.0 programming language. The product in the form of this application can be used more practically to solve CVRPTW problems using the GVNS algorithm.Keywords: Capacitated Vehicle Routing Problem with Time Windows (CVRPTW), General Variable Neighborhood Search (GVNS) Algorithm, Randomized Variable Neighborhood Descent (RVND)
ALGORITMA VARIABLE NEIGHBORHOOD DESCENT (VND) PADA VEHICLE ROUTING PROBLEM WITH SIMULTANEOUS DELIVERY AND PICKUP (VRPSDP) DAN IMPLEMENTASINYA Yulio Christopher; Sapti Wahyuningsih; Darmawan Satyananda
Jurnal Kajian Matematika dan Aplikasinya (JKMA) Vol 2, No 1 (2021): January
Publisher : UNIVERSITAS NEGERI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um055v2i12021p5-13

Abstract

Vehicle Routing Problem with Simultaneous Delivery and Pickup (VRPSDP) is a variant of Vehicle Routing Problem (VRP). VRPSDP has special constraints, namely requests and returns are carried out simultaneously. In this article we will use the Variable Neighborhood Descent (VND) algorithm to solve VRPSDP problems. There are two steps taken to use the VND algorithm on VRPSDP, namely finding an initial solution with the Insertion Heuristic algorithm and improving the position of the customer by using the neighborhood operator on the VND algorithm. The implementation of the VND algorithm on VRPSDP has been successfully made using the Borland Delphi 7.0 programming language. Inputs contained in the program are point position, distance between points, customer requests and returns and vehicle capacity. The output contained in the program in the form of routes that have been completed using an algorithm and output in the form of images of the final solution that has been obtained. Based on the results obtained, an example with 6 customers produces 3 routes with a total distance of 266 km, while an example with 10 customers produces 4 routes with a total distance of 100 km.
ALGORITMA GRAVITIONAL EMULATION LOCAL SEARCH PADA CVRP DAN IMPLEMENTASINYA Febri Nur Azis; Sapti Wahyuningsih; Darmawan Satyananda
Jurnal Kajian Matematika dan Aplikasinya (JKMA) Vol 3, No 1 (2022): January
Publisher : UNIVERSITAS NEGERI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um055v3i12022p23-29

Abstract

Permasalahan optimalisasi distribusi dapat dipecahkan dengan menggunakan algoritma pada varian Vehicle Routing Problem (VRP). Salah satu varian dari VRP adalah Capacitated Vehicle Routing Problem (CVRP) yaitu dengan tambahan kendala kapasitas kendaraan yang identik. Algoritma Gravitational Emulation Local Search (GELS) dapat digunakan untuk menentukan solusi CVRP. Algorima GELS merupakan gabungan dari algoritma genetika dan local search (best improvement local search). Pada artikel ini dibahas langkah algoritma dan diimplementasikan ke dalam computer menggunakan aplikasi Borland Delphi 7.  Input program berupa ukuran populasi, probabilitas crossover, probabilitas mutasi, maksimum iterasi, kapasitas kendaraan, banyaknya titik, dan permintaan setiap customer. Output berupa hasil rute dengan jarak yang ditempuh serta divisualisasi rutenya dengan gambar graph. .Diberikan contoh penyelesaian permasalahan dengan contoh 7 titik terdiri dari satu depot dan enam customer. Hasil tampilan program berupa matrik bobot titik, permintaan, dan hasil berupa rute optimal. Aplikasi program GELS pada CVRP secara praktis dapat digunakan untuk penyelesaian optimasi distribusi.