Integrated operational planning model, considering optimal delivery routing, incentives and electric vehicle aggregated demand management

Diaz-Cachinero, Pablo; Muñoz-Hernández, José Ignacio; Contreras, Javier

doi:10.1016/j.apenergy.2021.117698

Cited by 20 publications

(8 citation statements)

References 30 publications

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“…On this account, there have been a fair number of scholars making efforts to conduct research into the routing problem of EVs in the past few years. For instance, the EVs’ delivery routing and energy management (Diaz-Cachinero et al , 2021), the requirements of EV recharging operations (Zhang et al , 2018), energy-saving routes of EVs (Shao et al , 2018), etc. A substantial number of models and methods have been applied into this research field for the past decade, as EVs hold prominent future and practical significance over fuel-powered vehicles, and meet the governments’ regulations to reduce GHG emissions (Qin et al , 2021).…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic cyclic kitting part-feeding scheduling for mixed-model assembly line by a hybrid quantum-behaved particle swarm optimization

Zhou¹,

Huang²

2023

RIA

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Purpose The purpose of this paper is to cut down energy consumption and eliminate production waste on mixed-model assembly lines. Therefore, a supermarket integrated dynamic cyclic kitting system with the application of electric vehicles (EVs) is introduced. The system resorts to just-in-time (JIT) and segmented sub-line assignment strategies, with the objectives of minimizing line-side inventory and energy consumption. Design/methodology/approach Hybrid opposition-based learning and variable neighborhood search (HOVMQPSO), a multi-objective meta-heuristics algorithm based on quantum particle swarm optimization is proposed, which hybridizes opposition-based learning methodology as well as a variable neighborhood search mechanism. Such algorithm extends the search space and is capable of obtaining more high-quality solutions. Findings Computational experiments demonstrated the outstanding performance of HOVQMPSO in solving the proposed part-feeding problem over the two benchmark algorithms non-dominated sorting genetic algorithm-II and quantum-behaved multi-objective particle swarm optimization. Additionally, using modified real-life assembly data, case studies are carried out, which imply HOVQMPSO of having good stability and great competitiveness in scheduling problems. Research limitations/implications The feeding problem is based on static settings in a stable manufacturing system with determined material requirements, without considering the occurrence of uncertain incidents. Current study contributes to assembly line feeding with EV assignment and could be modified to allow cooperation between EVs. Originality/value The dynamic cyclic kitting problem with sub-line assignment applying EVs and supermarkets is solved by an innovative HOVMQPSO, providing both novel part-feeding strategy and effective intelligent algorithm for industrial engineering.

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Section: Literature Reviewmentioning

confidence: 99%

Dynamic cyclic kitting part-feeding scheduling for mixed-model assembly line by a hybrid quantum-behaved particle swarm optimization

Zhou¹,

Huang²

2023

RIA

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“…In [5], a hybrid AC/DC TEP model under high penetration of RESs incorporating BES devices is presented. The research works proposed in [6][7][8] investigate the impact of EVs [6], or DRPs [7,8] on power system operation and planning. An interlink between EV routing and optimal charging strategy in power system is developed in [6].…”

Section: Introductionmentioning

confidence: 99%

“…The research works proposed in [6][7][8] investigate the impact of EVs [6], or DRPs [7,8] on power system operation and planning. An interlink between EV routing and optimal charging strategy in power system is developed in [6]. The capability of DRPs for cost and emission reduction in generation and transmission expansion is addressed in [7].…”

Section: Introductionmentioning

confidence: 99%

Coordinated expansion planning of transmission and distribution systems integrated with smart grid technologies

Moradi‐Sepahvand

Amraee

Aminifar

et al. 2023

International Journal of Electrical Power & Energy Systems

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“…Xiong et al [12] developed an integrated and personalized traveler information scheme to stimulate an energy efficient mobility decision. Aiming to obtain a better routing and charging scheme, Diaz et al [14] proposed an incentive scheme, which grants more space to the EV demand-aggregator to devise a better operation scheme by determining the optimal charging time. However, these incentive schemes investigated in previous papers are solely used in either routing or charging applications, and there is no research publication on the joint optimization of the EV routing decisions, charging schedules, and incentive mechanism design problem.…”

Section: Introductionmentioning

confidence: 99%

Joint Routing and Charging Problem of Electric Vehicles With Incentive-Aware Customers Considering Spatio-Temporal Charging Prices

Yao

Chen

Salazar

et al. 2023

IEEE Trans. Intell. Transport. Syst.

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Integrated operational planning model, considering optimal delivery routing, incentives and electric vehicle aggregated demand management

Cited by 20 publications

References 30 publications

Dynamic cyclic kitting part-feeding scheduling for mixed-model assembly line by a hybrid quantum-behaved particle swarm optimization

Dynamic cyclic kitting part-feeding scheduling for mixed-model assembly line by a hybrid quantum-behaved particle swarm optimization

Coordinated expansion planning of transmission and distribution systems integrated with smart grid technologies

Joint Routing and Charging Problem of Electric Vehicles With Incentive-Aware Customers Considering Spatio-Temporal Charging Prices

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