Optimization of Multi-Products Distribution by Tabu Search Algorithm (Case Study: Fuel Distribution)

Main Article Content

Sri Wulandari
Norma Puspitasari

Abstract

Aims: Determine the vehicle s fuel distribution as distributing case of multi-product based on       the number of routes and the total mileage optimal manner using a split delivery tabu search algorithm.

Study Design: Trial percentage loading capacity of the three types of fuel to determine the percentage which gives optimum results.

Place and Duration of Study: Indonusa Surakarta Polytechnic to make the application of a tabu search algorithm to determine the route and calculate the total mileage of the vehicle. The time required 1 month.

Methodology: In this study as a central depot supplier number one, the number of consumers who have served are 19, types of products to be distributed is 3, and the type of transport vehicle used is one where vehicles are not restricted. There are 37 scenarios percentage payload capacity tested in this study to find the percentage of transport capacity which gives optimum results.

Results: The results showed that for three types of fuel distribution to 19 customers, scenarios percentage of premium transport capacity of 25%, 18% kerosene, diesel fuel 57% provide optimal results. Optimal results based on the number of routes of distribution and total mileage. The amount of the distribution as much as 5 routes with a total distance is 9.727 nautical miles.

Conclusion: Tabu search algorithm can be used to complete the Split Delivery Vehicle Routing Problem in the case of multi-product distribution by creating a scenario type of fuel carrying capacity of each product.

Keywords:
Vehicle routing problem, split delivery, multi-products, tabu search.

Article Details

How to Cite
Wulandari, S., & Puspitasari, N. (2020). Optimization of Multi-Products Distribution by Tabu Search Algorithm (Case Study: Fuel Distribution). Asian Journal of Research in Computer Science, 5(2), 1-9. https://doi.org/10.9734/ajrcos/2020/v5i230129
Section
Case study

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