In an era of sustainable development, considerable emphasis has been put onto energy saving, environment friendly, and social welfare as well as productivity in the manufacturing sector. In this work, an unrelated parallel manufacturing setting with time-of-use (TOU) electricity price is explored, with an aim to reduce the electricity cost and increase productivity simultaneously. A nonlinear mathematical programming model is formulated to exploit the special structure of the scheduling problem, where the quadratic constraints are reformulated as second-order-cone (SOC) constraints, and several tailored cutting planes are introduced to further tighten the feasible region of the problem. Then, the original scheduling problem is transformed into several single-machine scheduling problems with TOU electricity price, which could be relaxed as a single-objective programming problem, and it could be solved rapidly via commercial solvers, such as CPLEX. Based on the optimal solution of the relaxed problem, an approximate algorithm is proposed, where a special rounding technique is employed to assign jobs to the unrelated parallel machines in a local search manner. Furthermore, a lower bound model is constructed by eliminating the nonpreemption constraint, and an iteration-based algorithm is devised to obtain the optimal solution of the lower bound problem. Meanwhile, a dispatch rule-based approach is proposed to provide an upper bound of the scheduling problem with TOU constraint. In the numerical analysis section, the proposed approximate algorithm is validated through extensive testing on various scales of instances, different emphasis on productivity and electricity price, and under two typical TOU electricity pricing policies. It is observed that the gap between the proposed approximate algorithm and CPLEX is mostly within 4%, and the lower/upper bound methods could obtain a relaxed/feasible solution within 0.01 s.

Door-to-door delivery is becoming more prevalent in practice. However, crowdsourcing couriers' uncertainties (delivery distance, monthly income, and the monthly volume of tasks) make it hard for logistics companies to maintain a stable crowdsourcing couriers' participation rate and guarantee a good level of delivery coverage rate. To solve this problem, this paper proposed the crowdsourcing delivery optimization model, which considers the bounded rationality of crowdsourcing couriers, analyses the crowdsourcing couriers' participation rate under three crowdsourcing couriers' uncertainties, and helps logistics companies to decrease the delivery cost by adjusting the delivery price per parcel and delivery distance while guaranteeing a certain level of delivery coverage rate. Further, this paper combined the whale optimization algorithm (WOA) with the model to design a heuristic algorithm for solving the crowdsourcing delivery problem. The experiments were conducted according to a data set from Beijing (China). Experiment results shows that 4.07 million USD a month is enough to provide door-to-door delivery services in 94.22% area of the city, which is feasible for giant companies.

Background: Airway remodelling plays an important role in the pathogenesis of chronic obstructive pulmonary disease (COPD). Epithelial–mesenchymal transition (EMT) is a significant process during the occurrence of airway remodelling. Increasing evidence suggests that glucose transporter 3 (GLUT3) is involved in the epithelial mesenchymal transition (EMT) process of various diseases. However, the role of GLUT3 in EMT in the airway epithelial cells of COPD patients remains unclear. Methods: We detected the levels of GLUT3 in the peripheral lung tissue of COPD patients and cigarette smoke (CS)-exposed mice. Two Gene Expression Omnibus GEO datasets were utilised to analyse GLUT3 gene expression profiles in COPD. Western blot and immunofluorescence were used to detect GLUT3 expression. In addition, we used the AAV9-GLUT3 inhibitor to reduce GLUT3 expression in the mice model. Masson’s staining and lung function measurement were used detect the collagen deposition and penh in the mice. A cell study was performed to confirm the regulatory effect of GLUT3. Inhibition of GLUT3 expression with siRNA, Western blot, and immunofluorescence were used to detect the expression of E-cadherin, N-cadherin, vimentin, p65, and ZEB1. Results: Based on the GEO data set analysis, GLUT3 expression in COPD patients was higher than in non-smokers. Moreover, GLUT3 was highly expressed in COPD patients, CS exposed mice, and BEAS-2B cells treated with CS extract (CSE). Further research revealed that down-regulation of GLUT3 significantly alleviated airway remodelling in vivo and in vitro. Lung function measurement showed that GLUT3 reduction reduced airway resistance in experimental COPD mice. Mechanistically, our study showed that reduction of GLUT3 inhibited CSE-induced EMT by down-regulating the NF-κB/ZEB1 pathway. Conclusion: We demonstrate that CS enhances the expression of GLUT3 in COPD and further confirm that GLUT3 may regulate airway remodelling in COPD through the NF-κB/ZEB1 pathway; these findings have potential value in the diagnosis and treatment of COPD. The down-regulation of GLUT3 significantly alleviated airway remodelling and reduced airway resistance in vivo. Our observations uncover a key role of GLUT3 in modulating airway remodelling and shed light on the development of GLUT3-targeted therapeutics for COPD.