Multi-objective sustainable supply chain network optimization based on chaotic particle-Ant colony algorithm.

For the optimal design of the sustainable supply chain network, considering the comprehensiveness of the problem factors, considering the three aspects of economy, environment and society, the goal is to minimize the establishment cost, minimize the emission of environ-mental pollution and maximize the number of labor. A mixed integer programming model is established to maximize the efficiency of the supply chain network. The innovation of this paper, first, is to consider the impact of economic, environmental and social benefits in a continuous supply chain, where the environmental benefits not only consider carbon emissions but also include the emissions of plant wastewater, waste and solid waste as influencing factors. Second, a multi-objective fuzzy affiliation function is constructed to measure the quality of the model solution in terms of the overall satisfaction value. Finally, the chaotic particle ant colony algorithm is proposed, and the problem of premature convergence in the operation of the particle swarm algorithm is solved. Experimental results show that the PSCACO algorithm proposed in this paper is compared with MOPSO, CACO and NSGA-II algorithms, and the convergence effect of the algorithm is concluded to be more effective to verify the effectiveness and feasibility of chaotic particle ant colony algorithm for solving multi-objective functions, which proposes a new feasible solution for the supply chain management.

Quality Prediction of Fused Deposition Molding Parts Based on Improved Deep Belief Network.

Tensile strength, warping degree, and surface roughness are important indicators to evaluate the quality of fused deposition modeling (FDM) parts, and their accurate and stable prediction is helpful to the development of FDM technology. Thus, a quality prediction method of FDM parts based on an optimized deep belief network was proposed. To determine the combination of process parameters that have the greatest influence on the quality of FDM parts, the correlation analysis method was used to screen the key quality factors that affect the quality of FDM parts. Then, we use 10-fold cross-validation and grid search (GS) to determine the optimal hyperparameter combination of the sparse constrained deep belief network (SDBN), propose an adaptive cuckoo search (ACS) algorithm to optimize the weights and biases of the SDBN, and complete the construction of prediction model based on the above work. The results show that compared with DBN, LSTM, RBFNN, and BPNN, the ACS-SDBN model designed in this article can map the complex nonlinear relationship between FDM part quality characteristics and process parameters more effectively, and the CV verification accuracy of the model can reach more than 95.92%. The prediction accuracy can reach more than 96.67%, and the model has higher accuracy and stability.

Efficacy of the association liver partition and portal vein ligation for staged hepatectomy for the treatment of solitary huge hepatocellular carcinoma: a retrospective single-center study.

BACKGROUND: The feasibility of association liver partition and portal vein ligation for staged hepatectomy (ALPPS) for solitary huge hepatocellular carcinoma (HCC, maximal diameter ≥ 10 cm) remains uncertain. This study aims to evaluate the safety and the efficacy of ALPPS for patients with solitary huge HCC. METHODS: Twenty patients with solitary huge HCC who received ALPPS during January 2017 and December 2019 were retrospectively analyzed. The oncological characteristics of contemporaneous patients who underwent one-stage resection and transcatheter arterial chemoembolization (TACE) were compared using propensity score matching (PSM). RESULTS: All patients underwent complete two-staged ALPPS. The median future liver remnant from the ALPPS-I stage to the ALPPS-II stage increased by 64.5% (range = 22.3-221.9%) with a median interval of 18 days (range = 10-54 days). The 90-day mortality rate after the ALPPS-II stage was 5%. The 1- and 3-year overall survival (OS) rates were 70.0% and 57.4%, respectively, whereas the 1- and 3-year progression-free survival (PFS) rates were 60.0% and 43.0%, respectively. In the one-to-one PSM analysis, the long-term survival of patients who received ALPPS was significantly better than those who received TACE (OS, P = 0.007; PFS, P = 0.011) but comparable with those who underwent one-stage resection (OS, P = 0.463; PFS, P = 0.786). CONCLUSION: The surgical outcomes of ALPPS were superior to those of TACE and similar to those of one-stage resection. ALPPS is a safe and effective treatment strategy for patients with unresectable solitary huge HCC.