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All Journal Jurnal Penamas Adi Buana PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Contemporary Mathematics and Applications (ConMathA) Tensor: Pure and Applied Mathematics Journal
Edi Winarko
Universitas Airlangga
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Journal : Tensor: Pure and Applied Mathematics Journal

 1 
Flower Pollination Algorithm for Vehicle Routing Problem with Time Windows (VRPTW) Asri Bekti Pratiwi; Ismi Yayuk Rakhmawati; Edi Winarko
Tensor: Pure and Applied Mathematics Journal Vol 2 No 2 (2021): Tensor : Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol2iss2pp45-52

Abstract

Vehicle Routing Problem with Time Windows (VRPTW) is a vehicle route deciding problem that is used in order to serve customer who involved more than one vehicle with a limited time, so as a minimum distance route is obtained without disobeying vehicle capacity cargo restriction and time range. Flower Pollination Algorithm (FPA) is an algorithm which inspires from nature and that is flower pollination process toward a plant. Within an FPA, there are two main steps to use, they are global flower pollination and local flower pollination. Those two steps are determined by using switch probability parameter. This program is made in Java language program to apply FPA in solving VRPTW which is implemented in three example cases, they are small-scale datum with 25 customers, medium-scale datum with 50 customers, and big-scale datum with 100 customers. According to the results, it can be concluded that the larger number of flowers and iterations can affect the number of total minimum travel distance become smaller. Furthermore, a better total minimum travel distances also will be obtained if the value of switch probability parameter is larger.
Penyelesaian Unit Commitment Problem (UCP) Menggunakan Algoritma Genetika Whardhana, Aisyah Fadhilah; Pratiwi, Asri Bekti; Winarko, Edi
Tensor: Pure and Applied Mathematics Journal Vol 5 No 2 (2024): Tensor: Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol5iss2pp93-104

Abstract

The purpose of this research is to solve the Unit Commitment Problem (UCP), which is a critical task in power system optimization. The UCP involves determining the optimal scheduling of power generating units over a specified time horizon to meet the electricity demand while minimizing costs and satisfying operational constraints. In this study, a Genetic Algorithm (GA) method is proposed to solve the UCP efficiently. GA is inspired by the process of natural selection and evolution and is often used to solve complex optimization problems where traditional methods may be inefficient. The algorithm proceeds through several steps, namely parameters initialization, generating population, modification, calculating fitness function, parent selection, crossover, and mutation. The implementation of GA to solve UCP using C++ includes four different scenarios: a system with 4 units, 5 units, 10 units, and 26 units. The results obtained from the implementation of the GA on the different data sets indicate that the more iterations and the bigger initial population, the smaller the solution in the form of the total cost incurred.
Co-Authors Asri Bekti Pratiwi, Asri Bekti Auli Damayanti Derby Prayogo Samdean Dicky Zulfikar Zurkarnain Herry Suprajitno Ilham Ramadhani Inna Kuswandari Ismi Yayuk Rakhmawati Nenik Estuningsih, Nenik Nur Faiza Radifan Darari Sofiah Ishlakhul Abda Wahyuni, Yayuk Whardhana, Aisyah Fadhilah Yayuk Wahyuni