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Abstract Task scheduling (TS) and multi-agent-path-finding (MAPF) are two cruxes of pickup-and-delivery in automated warehouses. In this paper, the two cruxes are optimized simultaneously. Firstly, the system model, task model, and path model are established, respectively. Then, a task scheduling algorithm based on enhanced HEFT, a heuristic MAPF algorithm and a TS- MAPF algorithm are proposed to solve this combinatorial optimization problem. In EHEFT, a novel rank priority rule is used to determine task sequencing and task allocation. In MAPF algorithm, a CBS algorithm with priority rules is designed for path search. Subsequently, the TS-MAPF algorithm which combines EHEFT and MAPF is proposed. Finally, the proposed algorithms are tested separately against relevant typical algorithms at different scales. The experimental results indicate that the proposed algorithms exhibited good performance.

Nuclear factor erythroid 2-related factor 2 (Nrf2) is an important transcriptional regulator that plays a protective role against various cardiovascular diseases. Omaveloxolone is a newly discovered potent activator of Nrf2 that has a variety of cytoprotective functions. However, the potential role of omaveloxolone in the process of pathological cardiac hypertrophy and heart failure are still unknown. In this study, an isoproterenol (ISO)-induced pathological cardiac hypertrophy model was established to investigate the protective effect of omaveloxolone in vivo and in vitro. Our study first confirmed that omaveloxolone administration improved ISO-induced pathological cardiac hypertrophy in mice and neonatal cardiomyocytes. Omaveloxolone administration also diminished ISO-induced cardiac oxidative stress, inflammation and cardiomyocyte apoptosis. In addition, omaveloxolone administration activated the Nrf2 signaling pathway, and Nrf2 knockdown almost completely abolished the cardioprotective effect of omaveloxolone, indicated that the cardioprotective effect of omaveloxolone was directly related to the activation of the Nrf2 signaling. In summary, our study identified that omaveloxolone may be a promising therapeutic agent to mitigate pathological cardiac hypertrophy. [ABSTRACT FROM AUTHOR]

Many methods have been developed to study nonparametric function-on-function regression models. Nevertheless, there is a lack of model selection approach to the regression function as a functional function with functional covariate inputs. To study interaction effects among these functional covariates, in this article, we first construct a tensor product space of reproducing kernel Hilbert spaces and build an analysis of variance (ANOVA) decomposition of the tensor product space. We then use a model selection method with the L 1 criterion to estimate the functional function with functional covariate inputs and detect interaction effects among the functional covariates. The proposed method is evaluated using simulations and stroke rehabilitation data. [ABSTRACT FROM AUTHOR]

The crane & shuttle-based storage and retrieval system (C&SBS/RS) is the first automated warehouse technology that supports pallet picking, case picking and item picking. In the C&SBS/RS, aisle-captive cranes perform pallet picking, while tier-captive shuttles handle cases and items picking. To balance picking tasks, we propose an order dividing algorithm to fulfil required specific picking sequences. The optimisation objective is to minimise the order line picking time. Therefore, we modelled and analyzed the C&SBS/RS and considered single and dual command cycles for each resource (i.e. cranes, rail-guided vehicles, shuttles and lifters) separately according to their respective operation processes. Finally, numerical experiments were conducted to analyze impact factors and a real case to verify the power of the proposed order dividing algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we address a multiload AGVs workshop scheduling problem with limited buffer capacity. This has important theoretical research value and significance in the manufacturing field in considering the efficient multiload AGVs widely used today, and in the limited buffer area in production practice. To minimize the maximum completion time, an improved ant colony optimization-simulated annealing algorithm based on a multiattribute dispatching rule is proposed. First, we introduce a multiattribute dispatching rule, which combines two attributes, delivery completion time and input queue through dynamic weights that are determined by the information about the system, using the multiattribute dispatching rule to construct the initial solution. Then, with the ant colony optimization-simulated annealing algorithm as the basic framework, we propose a method for calculating transfer probability based on the multiattribute dispatching rule, which obtains heuristic information through the proposed rule. Further, we propose a path branch mechanism and dynamic equilibrium mechanism, aiming to efficiently construct the ant path and dynamically adjust ant path distribution. We propose a key job strategy and design a 2-opt neighborhood search method based on key jobs. Data experiments demonstrate the multiattribute dispatching rule is superior over other heuristic dispatching rules; the algorithm improvement strategies proposed are effective when used simultaneously or separately. Further, the proposed algorithm in this paper is superior over other heuristic algorithms and adapts to all kinds of instances. [ABSTRACT FROM AUTHOR]

In this paper, we propose a nonconcave penalized M-estimation of the least absolute relative errors (penalized M-LARE) method for a sparse multiplicative regression model, where the dimension of model can increase with the sample size. Under certain appropriate conditions, the consistency and asymptotic normality for the penalized M-LARE estimator are established. Simulations and a real data analysis are in support of our theoretical results and illustrate that the proposed method performs well. [ABSTRACT FROM AUTHOR]