Implementation of the Model Capacited Vehicle Routing Problem with Time Windows with a Goal Programming Approach in Determining the Best Route for Goods Distribution
DOI: 10.20956/jmsk.v17i2.11107
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Summary
This study addresses the optimization of goods distribution routes for a logistics company, specifically focusing on the Capacitated Vehicle Routing Problem with Time Windows (CVRPTW). The research is motivated by the need to move beyond driver experience-based routing, which often fails to balance multiple conflicting objectives such as cost, time, vehicle capacity, and customer service levels. The authors aim to determine the most efficient routes for distributing goods from a single depot to multiple customers while adhering to strict constraints, including vehicle capacity limits and specific customer operating hours. The methodology employs a goal programming approach to solve the multi-objective CVRPTW model. The study uses a case study of CV. Oke Jaya, a company serving 25 customers across Serang, Pandeglang, Rangkasbitung, and Cikande using a single freight vehicle with a 2,000 kg capacity. Data collection involved calculating distances and travel times via Google Maps, estimating fuel costs based on a rate of Rp 583 per kilometer, and determining service times based on employee estimates. The mathematical model was formulated to minimize total travel cost and distribution time while maximizing the number of served customers and vehicle capacity utilization. The model was implemented and solved using LINGO 11.0 software, incorporating constraints such as single visits per customer, route continuity, and adherence to customer time windows. The results identified four optimal routes for the distribution network. The total cost for these routes was Rp 233,000, with a total distribution time of 17 hours and 57 minutes. The routes successfully distributed a total of 6,150 kg of goods, effectively maximizing the vehicle's capacity across multiple trips. Specifically, Route 1 took 3 hours and 7 minutes, Route 2 took 3 hours and 20 minutes, Route 3 took 6 hours and 44 minutes, and Route 4 took 4 hours and 40 minutes. The analysis revealed that Routes 1 and 2 were short enough to be completed within a single day, while Routes 3 and 4 required separate days due to their longer durations. The significance of this study lies in its demonstration that goal programming can effectively resolve complex, multi-objective routing problems with time window constraints. For CV. Oke Jaya, the model provided a structured, optimal solution that replaced heuristic methods, resulting in a feasible schedule requiring three working days to serve all 25 customers. The findings highlight the practical application of mathematical modeling in logistics to enhance efficiency, reduce costs, and ensure timely service within operational constraints.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-20 |
| archive | success | unpaywall | — | — | 2 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-20 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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