Scientific mapping and research perspectives of the vehicle routing problem: An approach from sustainability strategies

Sustainable Futures, Journal Year: 2024, Volume and Issue: unknown, P. 100390 - 100390

Published: Nov. 1, 2024

Language: Английский

Optimization of emission scheduling in microgrids with electric vehicle integration

Sustainable Energy Research, Journal Year: 2024, Volume and Issue: 11(1)

Published: Nov. 5, 2024

In the context of continuous development new energy vehicles, an increasing number electric vehicles (EVs) are being integrated into microgrids, which impacts operation microgrids. It is necessary to analyze emission scheduling microgrids connected with EVs ensure smooth and reliable EV integration. This paper aims realize optimal microgrid scheduling. article took case connection through orderly charging discharging. Firstly, mathematical models for each output unit in were established. Then, aiming minimize both operational cost pollution treatment microgrid, dispatch optimization model was developed. The whale algorithm (WOA) chosen as solving algorithm, improved WOA (IWOA) obtained by optimizing original terms population initialization position updating parameters. An example analysis revealed that IWOA demonstrated superior performance compared other algorithms. scenario discharging, discharged during peak hours charged off-peak balance load. operating 967.25 yuan, 241.52 resulting a total 1208.77 yuan. These results confirm reliability proposed its applicability

Language: Английский

Stage-Specific Multi-Objective Five-Element Cycle Optimization Algorithm in Green Vehicle-Routing Problem with Symmetric Distance Matrix: Balancing Carbon Emissions and Customer Satisfaction

Symmetry, Journal Year: 2024, Volume and Issue: 16(10), P. 1305 - 1305

Published: Oct. 3, 2024

This study presents a bi-objective optimization model for the Green Vehicle-Routing Problem in cold chain logistics, with focus on symmetric distance matrices, aiming to minimize total costs, including carbon emissions, while maximizing customer satisfaction. To address this complex challenge, we developed Stage-Specific Multi-Objective Five-Element Cycle Optimization algorithm (MOFECO-SS), which dynamically adjusts strategies across different stages of process, thereby enhancing overall efficiency. Extensive comparative analyses existing algorithms demonstrate that MOFECO-SS consistently outperforms solving multi-objective model, particularly reducing costs and emissions maintaining high levels The nature matrix further aids achieving balanced optimized route planning. results highlight offers decision-makers flexible planning options balance cost efficiency environmental sustainability, ultimately improving effectiveness logistics operations.

Language: Английский