Carbon Transaction-Based Location-Routing- Inventory Optimization for Cold Chain Logistics

Li, Kang; Li, Dan; Wu, Daqing

doi:10.1016/j.aej.2022.01.062

Cited by 37 publications

(12 citation statements)

References 23 publications

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“…They used the cloud particle swarm optimization algorithm to solve the model and select a viable location for a new center. Li et al ( 2022 ) suggested a carbon transaction-based integrated LRIP model. To solve the model, the NSGA-II was enhanced.…”

Section: Literature Reviewmentioning

confidence: 99%

Designing a sustainable fish closed-loop supply chain network under uncertainty

Fasihi

Tavakkoli–Moghaddam

Hajiaghaei–Keshteli

et al. 2023

Environ Sci Pollut Res

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There is increasing attention to the sustainable development of supply chain (SC) and reverse logistics (RL) in the contemporary competitive economy, notably in the food sector, by scholars and stakeholders. This study investigates a sustainable closed-loop supply chain (CLSC) for fish due to its high value in the family food basket, its perishability, and the importance of waste product recycling. A multi-objective mathematical model is developed under uncertainty and sustainability criteria to optimize production rates with the aim of better distribution among different demand markets, total costs, social issues, and negative environmental effects (e.g., CO 2 emissions and unused/waste products). A combination of exact, meta-heuristic, and hybrid meta-heuristic algorithms are used to solve the suggested model. Then, the optimal solutions are found using the Taguchi method by evaluating the best initial replies. The solutions are evaluated based on various performance metrics. The analysis of variance (ANOVA) and the “filtering/displaced ideal solution” methods determine the best solution approach. Moreover, a case study with a trout CLSC in Northern Iran is examined. In addition, the Lingo software utilizes the ε-constraint method to evaluate and check the performance of the algorithms under different levels of uncertainty. Finally, sensitivity analyses are carried out to confirm the efficacy of the proposed algorithms. The findings demonstrate the proposed network’s outstanding consistency with the algorithms used and its application and efficiency.

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Section: Literature Reviewmentioning

confidence: 99%

Designing a sustainable fish closed-loop supply chain network under uncertainty

Fasihi

Tavakkoli–Moghaddam

Hajiaghaei–Keshteli

et al. 2023

Environ Sci Pollut Res

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show abstract

“…By analyzing existing research, it is found that many scholars convert carbon emission into carbon emission cost when studying cold chain logistics vehicle routing problems (Li et al, 2019a). Li et al (2022b) and Hu et al (2021) adopted above approach, where the environment cost was obtained through the unit price and carbon emission determined based on emission factor. At present, this method for calculating carbon emission cost has become the research mainstream (Chen et al, 2019;.…”

Section: Cold Chain Logistics Vehicle Routing Problemmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

An electric vehicle routing model with charging stations consideration for sustainable logistics

Li,

Lim,

Xiong

et al. 2023

IMDS

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PurposeRecently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.Design/methodology/approachThis study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.FindingsThe result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.Research limitations/implicationsThe optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.Originality/valueIn prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

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“…Non-dominated sorting genetic algorithm II (NSGA-II) was proposed by Deb et al [38]. It was used to solve many problems, including scheduling [39,40], redundancy allocation [41,42], reducing carbon emissions [43], battery thermal management system management [44], passive heat supply tower management [45], and vehicle routing [46,47]. NSGA-II originated from the GA based on the natural evolution process, where the fittest individuals are selected for reproduction to produce offspring of the next generation via selection, crossover, and mutation.…”

Section: Non-dominated Sorting Genetic Algorithm II (Nsga-ii)mentioning

confidence: 99%

Application of a Non-Dominated Sorting Genetic Algorithm to Solve a Bi-Objective Scheduling Problem Regarding Printed Circuit Boards

Chang

Zheng

2022

Mathematics

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An unrelated parallel machine scheduling problem motivated by the scheduling of a printed circuit board assembly (PCBA) under surface mount technology (SMT) is discussed in this paper. This problem involved machine eligibility restrictions, sequence-dependent setup times, precedence constraints, unequal job release times, and constraints of shared resources with the objectives of minimizing the makespan and the total job tardiness. Since this scheduling problem is NP-hard, a mathematical model was first built to describe the problem, and a heuristic approach using a non-dominated sorting genetic algorithm (NSGA-II) was then designed to solve this bi-objective problem. Multiple near-optimal solutions were provided using the Pareto front solution and crowding distance concepts. To demonstrate the efficiency and effectiveness of the proposed approach, this study first tested the proposed approach by solving test problems on a smaller scale. It was found that the proposed approach could obtain optimal solutions for small test problems. A real set of work orders and production data was provided by a famous hardware manufacturer in Taiwan. The solutions suggested by the proposed approach were provided using Gantt charts to visually assist production planners to make decisions. It was found that the proposed approach could not only successfully improve the planning time but also provide several feasible schedules with equivalent performance for production planners to choose from.

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Carbon Transaction-Based Location-Routing- Inventory Optimization for Cold Chain Logistics

Cited by 37 publications

References 23 publications

Designing a sustainable fish closed-loop supply chain network under uncertainty

Designing a sustainable fish closed-loop supply chain network under uncertainty

An electric vehicle routing model with charging stations consideration for sustainable logistics

Application of a Non-Dominated Sorting Genetic Algorithm to Solve a Bi-Objective Scheduling Problem Regarding Printed Circuit Boards

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