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All Journal Jurnal Rekayasa Sistem Industri Jurnal Optimasi Sistem Industri International Journal of Computing Science and Applied Mathematics
Alberto, Giovano
Jurusan Teknik Industri Universitas Katolik Parahyangan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering

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Model Matematis untuk Multi-product Multi-warehouse Inventory Routing Problem Giovano Alberto
Jurnal Rekayasa Sistem Industri Vol. 12 No. 1 (2023): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (302.128 KB) | DOI: 10.26593/jrsi.v12i1.6371.27-34

Abstract

Every business always aims to make significant profits. The corporation can cut expenses in one way or another. Logistics is one of the most expensive operations, and two-thirds of its expenditures are related to inventory and transportation. Inventory and transportation challenges must be addressed simultaneously in the supply chain to achieve the best results.This problem is modeled in the inventory routing problem (IRP). The development of the IRP model still has gaps with real conditions. The IRP model designed has not yet discussed the Multi-product Multi-warehouse Inventory Routing Problem (MMIRP) model. MMIRP takes into account the conditions of the types of goods that need to be sent, which vary and there are several warehouses that have goods of different types in one period of time. The results obtained after completing the model are the number of vehicles used, the number of goods of each type shipped, the travel routes generated by each vehicle, and the large costs generated based on the route design and inventory at each location.
Dynamic Scoring and Costing in the Orienteering Problem: A Model Based on Length of Stay Giovano Alberto; Carles Sitompul
Jurnal Optimasi Sistem Industri Vol. 22 No. 2 (2023): Published in December 2023
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v22.n2.p114-125.2023

Abstract

In today's travel and tourism landscape, the role of travel agents has become increasingly complex as they are challenged to explore a variety of potential destinations. More specifically, the complicated task of planning itineraries that truly satisfy travellers puts travel agents in a crucial role, increasing the complexity of itinerary planning. This complexity is compounded not only by the multitude of possible destinations, but also by non-negotiable constraints such as cost and time. To address these challenges, the orienteering problem represents a fundamental mathematical model that provides a theoretical basis for understanding the nuanced difficulties faced by travel agents.This study ventures into a novel iteration of the orienteering problem, with a particular focus on optimizing travel satisfaction based on length of stay. A notable aspect of this variant is the inclusion of time and cost constraints in the route determination process. Using an integer programming model, the satisfaction scores for each location are described by a diminishing returns function linked to length of stay, while the costs associated with each location follow a linear function influenced by the same parameter. The application of this model is in a hypothetical scenario with 32 nodes, with the calculations facilitated by the FilMINT solver. A sensitivity analysis examines time and cost constraints and shows their decisive influence on the optimization of travel routes. The results of this research contribute significantly to a strategic framework and provide travel agencies with the opportunity to create itineraries that not only meet practical limits but, more importantly, increase traveller satisfaction.
An Application of Binary Cuckoo Search Algorithm to Orienteering Problem Alberto, Giovano; Tan, Alfian
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 7, No 2 (2021)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.v7i2.8663

Abstract

This research applies the cuckoo search metaheuristics model to find solutions to the Orienteering Problem (OP). The OP formulation is useful to model a situation in which someone wants to determine an optimal city route that is subject to a specified time constraint. OP can be categorized into NP Hard Problem which takes a very long time to analytically find the optimal solution as the number of entities involved increases. Therefore, metaheuristics often become an option to deal with this situation. A cuckoo search model based algorithm is developed in this research. An adjustment for discrete combinatorial problem is performed by adopting an idea of binary cuckoo search method. In addition, three types of local search methods are considered to improve the searching performance. This algorithm can eventually find better solutions for some of the 18 cases than two other benchmarked algorithms. Furthermore, experiment on model parameters shows that the worse nest fraction (P_alpha) affects the quality of solutions obtained.
Dynamic Scoring and Costing in the Orienteering Problem: A Model Based on Length of Stay Giovano Alberto; Carles Sitompul
Jurnal Optimasi Sistem Industri Vol. 22 No. 2 (2023): Published in December 2023
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.703 KB) | DOI: 10.25077/josi.v22.n2.p114-125.2023

Abstract

In today's travel and tourism landscape, the role of travel agents has become increasingly complex as they are challenged to explore a variety of potential destinations. More specifically, the complicated task of planning itineraries that truly satisfy travellers puts travel agents in a crucial role, increasing the complexity of itinerary planning. This complexity is compounded not only by the multitude of possible destinations, but also by non-negotiable constraints such as cost and time. To address these challenges, the orienteering problem represents a fundamental mathematical model that provides a theoretical basis for understanding the nuanced difficulties faced by travel agents.This study ventures into a novel iteration of the orienteering problem, with a particular focus on optimizing travel satisfaction based on length of stay. A notable aspect of this variant is the inclusion of time and cost constraints in the route determination process. Using an integer programming model, the satisfaction scores for each location are described by a diminishing returns function linked to length of stay, while the costs associated with each location follow a linear function influenced by the same parameter. The application of this model is in a hypothetical scenario with 32 nodes, with the calculations facilitated by the FilMINT solver. A sensitivity analysis examines time and cost constraints and shows their decisive influence on the optimization of travel routes. The results of this research contribute significantly to a strategic framework and provide travel agencies with the opportunity to create itineraries that not only meet practical limits but, more importantly, increase traveller satisfaction.
Co-Authors Carles Sitompul Tan, Alfian