Analysis of multi-objective vehicle routing problem with flexible time windows: The implication for open innovation dynamics

Abstract

Renewable energy has been a worldwide interest due to a growing energy demand as well as a mounting concern over the hostile impacts from traditional fuels. One of a direction for future renewable energy is the use of biofuel. In this research, we initially apply the K-means algorithm to evaluate the possible locations of collection sites at the upstream of the biofuel supply chain. Next, we propose the multi-objective vehicle routing problem model, in which flexible time windows are synchronized in the model. Additionally, our integrated model evaluates the perspective of socioeconomic by considering total cost – the surrogate criterion for economic aspect as well as the lateness for delivery and the maximum delivery time – the surrogate criteria for social aspect, into account. Finally, we apply a model to a regional case study based on the wood-biomass data of the biofuel supply chain in Thailand, in which the geographic information system is applied.

Keywords

• Biofuel supply chain
• Multi-objective optimization
• K-means algorithm
• Vehicle routing problem
• Flexible time windows
• Sustainability