Amount Of Resource Allocation Research Articles

Automated System for Managing Hospital Data Using RPA

Abstract: Healthcare systems contain multiple difficult tasks and strict regulations that require a considerable amount of resource allocation which causes high cost of operation, slower process and inefficiency. Healthcare professionals can address these problems by using the strength of automation and RPA thereby patient satisfaction can be improved. QR codes are fast becoming the go-to method for many organizations and businesses around the world. The reason complex management systems are using QR codes to manage their businesses better is that QR codes can help organize the overwhelming data gathered from customer and, on the other hand, give out information to users where it is due. Hospitals are some of the most challenging and complex organizations to manage and maintain. There are many variables to consider when running a hospital, such as patients, doctors, staff, drugs, labs. Automating the existing manual process of admission through computer software and hardware is the aim of hospital management system which enables faster access and manipulation of the valuable information through QR code.

Single machine resource allocation scheduling problems with deterioration effect and general positional effect.

This paper investigates single machine scheduling problems where the actual processing time of a job is dependent on its starting time, processing position and the amount of resource allocation. We present two unified models and provide a bicriteria analysis for the general scheduling criteria and the total weighted resource consumption. We consider two different versions for treating the two criteria and show that the unified models can be applied to solve scheduling problems under various due window assignment considerations. We prove that two different versions of the problems can be solved in polynomial time, respectively.

Solution algorithms for single-machine resource allocation scheduling with deteriorating jobs and group technology

ABSTRACTThis article deals with a single-machine resource allocation scheduling problem with deteriorating jobs. Under a group technology environment, the actual processing times of jobs are a convex resource allocation function of their starting time and the amount of resource allocation. The objective is to minimize the weighted sum of makespan and resource allocation cost. For two special cases, it is proved that the problem can be solved in polynomial time. For the general case of the problem, heuristic and branch-and-bound procedures are developed to solve the problem. Computational experiments are also performed to examine the effectiveness and the efficiency of the algorithms.

Research on common due window assignment flowshop scheduling with learning effect and resource allocation

ABSTRACTIn this article, the two-machine no-wait permutation flowshop scheduling problem with common due window assignment, learning effect and resource allocation is considered, wherein learning effect and resource allocation mean that the processing time of a job is a function of its position in a sequence and its amount of resource allocation. According to the common due window assignment method, each job is associated with a common due window, which is a decision variable. The goal is to determine the sequence of jobs, common due window starting time, due window size and resource allocation such that the linear weighted sum of job earliness, tardiness, due window size and resource cost is minimized. This article shows that the scheduling problem can be solved in polynomial time.

Resource constrained scheduling problems with general truncated sum-of-processing time dependent effect under single machine and unrelated parallel machines

This paper studies some scheduling problems with general truncated sum-of-processing time dependent effect under single machine and unrelated parallel machines. Under the single machine, we consider that the actual processing time of a job is bivariate, continuous and non-increasing convex function of the total processing time of the processed jobs, its position, the amount of resource allocation and control parameter. SLK due date assignment models are involved, in which the length of due window is the same. We present the polynomial time algorithms to find the optimal job sequence, the due date and resource allocations that minimizing including the slack due date, earliness cost, tardiness cost, resource consumption costs and makespan. Under the unrelated machines, we only consider no resource locations scheduling problems. Minimizing the total the machine load and minimizing the total completion time can also be solved in a polynomial time when the number of machines is fixed, respectively.

Health Equity and Adolescent Health: A Call to Action for the Society for Adolescent Health and Medicine

Health Equity and Adolescent Health: A Call to Action for the Society for Adolescent Health and Medicine

Matching plant and animal processes to alter nutrient supply in strip-grazed cattle: Timing of herbage and fasting allocation1

This work aimed to assess the impact of timing of herbage allocation and fasting on patterns of ingestive behavior, herbage intake, ruminal fermentation, nutrient flow to the duodenum, and site and extent of digestion. Treatments were daily herbage allocation in the afternoon (1500 h, AHA), morning (0800 h, MHA), AHA after 20 h of fasting (AHAF), and MHA after 20 h of fasting (MHAF). Four ruminally and duodenally fistulated heifers (279 +/- 99 kg of BW) individually strip-grazed wheat pastures in a Latin-square design. Eating, rumination, and idling behavior were recorded every 2 min, and bite and eating step rates were measured hourly while the heifers were grazing (11 h MHA and AHA; 4 h MHAF and AHAF). Ruminal DM pools were measured 4 times daily (0800, 1200, 1500, and 1900 h) to estimate daily herbage DMI and its pattern. Ruminal fluid was sampled at these same times and also at 2300 h. Duodenal digesta was sampled over 2 d to determine the site of herbage digestibility. Treatments did not affect daily herbage DMI (16.5 g/ kg of BW, SE = 0.0025; P > 0.05). However, they altered the eating pattern; the evening grazing bout of AHA and AHAF was greater (P < 0.05) and more intense (P < 0.05 for bite mass and rate, eating step, and intake rates). Ruminal nonglucogenic:glucogenic VFA ratio and pH were lower (P < 0.05) for AHA and AHAF during the evening. The flow of OM, N, microbial protein, and nonmicrobial OM to the duodenum did not vary (P > 0.05) among MHA, MHAF, and AHAF; however, it averaged 970, 40, 300, and 540 g/d, respectively, greater (P < 0.05) for AHA. Total tract digestibility did not differ (P > 0.05) for MHA, AHA, and AHAF, but was lower for MHAF (P < 0.05). Apparent ruminal digestion did not differ (P > 0.05) within fasted and nonfasted treatments; however, it was greater (P < 0.05) for fasted than nonfasted treatments. True OM ruminally digested did not differ (P > 0.05) among MHA, MHAF, and AHAF, but was greater (P < 0.05) for AHA. The results demonstrate the strong link between ingestion and digestion patterns, and its impact on nutrient supply. At the same amount of resource allocation, nutrient supply to grazing cattle can be modified through strategic grazing management.