Developing Algorithm of Periodic Vehicle Routing Problem (PVRP) For Solving Integrated Delivery And Installation Of Home Appliances

Salsabila, Shafiyah (2019) Developing Algorithm of Periodic Vehicle Routing Problem (PVRP) For Solving Integrated Delivery And Installation Of Home Appliances. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Distribution system is one of the important components in a company that needs to be managed effectively in terms of costs and service levels. Distribution system of home appliances company or a company that sell electronic appliances, furniture, and home improvement and lifestyle product have some unique complexities. The company is not only responsible for delivering products to the customer’s location but is also responsible for the product installation requested by the customer. To be able to synchronize the delivery and installation activities, the company needs an integrated routing and scheduling that can minimize the total costs. Periodic Vehicle Routing Problem (PVRP) is the tool chosen for solving integrated delivery and installation of home appliances because it can schedule delivery and installation daily within a specified period of time as well as assigning the installation technicians needed. The model is developed from the classic PVRP by adding synchronization of technician skills to the type of product installed and the range available visit days set by the customer. Route determination is made by heuristics method which consists of constructive heuristics and improvement heuristics. In this research, the computerized model is created using Visual Basic Application (VBA) in Microsoft Excel. The benefits of PVRP decision tools by optimizing the schedule combination between delivery and installation for all customers using improvement heuristics can save the total distribution cost up to 14.36% compared to the constructive heuristics results. However, as a drawback, this model requires very long computational time especially during calculations for bigger data sizes. When the number of customers are 30, 50, and 75 the average computational times increase by 272%, 1193%, and 2843% respectively compared to when the number of customers is 15. In addition, when the maximum number of iterations are set to 50 and 100, the average computational times increase by 72% and 310% respectively compared to when the maximum number of iterations is set to 30.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	delivery and installation, improvement heuristics, Periodic Vehicle Routing Problem, Vehicle Routing Problem with Synchronization Constraints
Subjects:	T Technology > T Technology (General) > T58.62 Decision support systems
Divisions:	Faculty of Industrial Technology > Industrial Engineering > 26201-(S1) Undergraduate Thesis
Depositing User:	Shafiyah Salsabila
Date Deposited:	22 Jul 2026 02:50
Last Modified:	22 Jul 2026 02:50
URI:	http://repository.its.ac.id/id/eprint/66408

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