Optimization of Flexible Production Logistics under Low Carbon Constraint

Abstract

Flexible production centring on machines or job-shops is necessary to meet the current trend of production and sales. By studying the energy consumption of production logistics, it is possible to minimize energy consumption and carbon emissions of the production process, without sacrificing production efficiency. The existing studies all try to optimize the logistics distribution. None of them attempt to optimize both production and logistics distribution parameters, and low carbon emission indices. Therefore, this paper explores the multi-objective optimization and carbon efficiency evaluation of flexible production logistics under low carbon constraint. Specifically, the constraint order between production logistics time, logistics quality, logistics cost, and low-carbon degree was determined, and the expressions of four linear programming models were given. Moreover, the carbon efficiency optimization of flexible production logistics was redefined, and a mathematical model was developed for the carbon efficiency optimization problem, which simultaneously optimizes carbon emissions and production indices. The proposed model was proved scientific through experiments.

Production Logistics in Industry 3.X: Bibliometric Analysis, Frontier Case Study, and Future Directions

“…From the perspective of green control of shop-level production logistics, Dai et al [82] constructed a multi-objective optimization model aiming at minimizing energy consumption and production time, and proposed an enhanced genetic algorithm (EGA) to solve the flexible job-shop scheduling problem considering logistics transport constraints between processes. Furthermore, in order to minimize energy consumption and carbon emissions in the process of production logistics without sacrificing production efficiency, Wang et al [83] studied the multi-objective optimization and carbon efficiency evaluation of flexible production logistics under low carbon constraints. By establishing a mathematical model of carbon efficiency optimization, both carbon emissions and production logistics indexes were optimized.…”

Dynamic Evaluation of Energy Carbon Efficiency in the Logistics Industry Based on Catastrophe Progression

“…The corresponding coefficients of incentives and punishments can be obtained from Equations ( 5) and ( 6), and the dynamic, comprehensive assessment value of the efficiency of the logistics industry's energy carbon emissions under fuzzy incentives and punishments was calculated by integrating Equation (7), as shown in Table 7. As seen from Table 7, the dynamically integrated assessment of the energy carbon efficiency of the logistics sector was mostly smaller than the dynamically integrated assessment of the energy carbon efficiency of the logistics sector without this condition in the presence of vague incentives and penalties.…”

“…In 2020, China's CO 2 emissions reached 9894 billion NDUs, accounting for 30.93% of the world's total CO 2 emissions and ranking first globally. Furthermore, in response to the long-term goal of improving the climate, China has already made many efforts in reducing carbon emissions [6][7][8]. The Chinese logistics industry is the second-largest carbon emitter after manufacturing.…”