Scheduling trucks in cross docking systems with temporary storage and dock repeat truck holding pattern using GRASP method

Cross docking play an important role in management of supply chains where items delivered to a warehouse by inbound trucks are directly sorted out, reorganized based on customer demands, routed and loaded into outbound trucks for delivery to customers without virtually keeping them at the warehouse. If any item is held in storage, it is usually for a short time, which is normally less than 24 hours. The proposed model of this paper considers a special case of cross docking where there is temporary storage and uses GRASP technique to solve the resulted problem for some realistic test problems. In our method, we first use some heuristics as initial solutions and then improve the final solution using GRASP method. The preliminary test results indicate that the GRASP method performs better than alternative solution strategies

An imperialist competitive algorithm for a bi-objective parallel machine scheduling problem with load balancing consideration

In this paper, we present a new Imperialist Competitive Algorithm (ICA) to solve a bi-objective unrelated parallel machine scheduling problem where setup times are sequence dependent. The objectives include mean completion time of jobs and mean squares of deviations from machines workload from their averages. The performance of the proposed ICA (PICA) method is examined using some randomly generated data and they are compared with three alternative methods including particle swarm optimization (PSO), original version of imperialist competitive algorithm (OICA) and genetic algorithm (GA) in terms of the objective function values. The preliminary results indicate that the proposed study outperforms other alternative methods. In addition, while OICA performs the worst as alternative solution strategy, PSO and GA seem to perform better

An imperialist competitive algorithm for a bi-objective parallel machine scheduling problem with load balancing consideration

In this paper, we present a new Imperialist Competitive Algorithm (ICA) to solve a bi-objective scheduling of parallel-unrelated machines where setup times are sequence dependent. The objectives include mean completion tasks and mean squares of deviations from machines workload from their averages. The performance of the proposed ICA (PICA) method is examined using some randomly generated data and they are compared with three alternative methods including particle swarm optimization (PSO), original version of imperialist competitive algorithm (OICA) and genetic algorithm (GA) in terms of the objective function values. The preliminary results indicate that the proposed study outperforms other alternative methods. In addition, while OICA performs the worst as alternative solution strategy, PSO and GA seem to perform better

Fat mass and obesity-associated gene (FTO) rs9939609 (A/T) polymorphism and food preference in obese people with low-calorie intake and non-obese individuals with high-calorie intake

Abstract The purpose of this study was to assess the connection between FTO rs9939609 (A/T) polymorphism and food preference. The study included 77 participants, 36 of whom were obese and had a low-calorie intake, and 41 non-obese participants with a high-calorie intake. Using a food frequency questionnaire (FFQ), the researchers calculated sweet and fatty food propensity scores. Genomic DNA was extracted from a peripheral blood sample from all participants, and FTO rs9939609 (A/T) polymorphism was assessed using standard methods. The study found no significant differences between the two groups in terms of sweet food preference (15.64 ± 10.53 in obese groups vs. 14.72 ± 7.95 in the non-obese group, p = 0.711) and fatty food preference (16.81 ± 8.84 vs. 17.27 ± 8.75; p = 0.833). Additionally, the study did not find any significant correlation between FTO rs9939609 (A/T) polymorphism and sweet and fatty food preferences in the fully adjusted models (p > 0.05). Therefore, the results of this study do not support the hypothesis of different food preferences

Endoplasmic reticulum stress PERK-ATF4-CHOP pathway is involved in non-alcoholic fatty liver disease in type 1 diabetic rats: The rescue effect of treatment exercise and insulin-like growth factor I

Endoplasmic Reticulum Stress (ERS) is a key factor in the development of Non-Alcoholic Fatty Liver Disease (NAFLD) in diabetes. The current study aimed to examine the effects of exercise and IGF-I on ERS markers in liver tissue. Rats were divided into five groups (n = 8 per group), including control (CON), diabetes (DIA), diabetes + exercise (DIA + EX), diabetes + IGF-I (DIA + IGF-I), and diabetes + exercise + IGF-I (DIA + EX + IGF-I). Type 1 diabetes was induced by an I.P. injection of streptozotocin (60 mg/kg). After 30 days of treatment with exercise or IGF-I alone or in combination, liver tissue was assessed for caspase 12, 8, and CHOP protein levels, and expression of ERS markers (ATF-6, PERK, IRE-1A) and lipid metabolism-involved genes (FAS, FXR, SREBP-1c) by western immunoblotting. In addition, for the evaluation of histopathological changes in the liver, Hematoxylin - Eosin and Masson's Trichrome staining were done. Compared to the control group, diabetes significantly caused liver fibrosis, induced ERS, increased caspase 12 and 8 levels in the liver, and changed expression levels of genes associated with lipid metabolism, including FAS, FXR, and SREBP-1c. Treatment with either exercise or IGF-I reduced fibrosis levels suppressed ER stress markers and apoptosis, and improved expression of genes associated with lipid metabolism. In addition, simultaneous treatment with exercise and IGF-I showed a synergistic effect compared to DIA + E and DIA + IGF-I. The results suggest that IGF-1 and exercise reduced liver fibrosis possibly by reducing ERS, creating adaptive ER stress status, and improving protein folding