Prediction of arrival times and human resources allocation for container terminal

2011 ◽  
Vol 13 (2) ◽  
pp. 142-173 ◽  
Author(s):  
Gianfranco Fancello ◽  
Claudia Pani ◽  
Marco Pisano ◽  
Patrizia Serra ◽  
Paola Zuddas ◽  
...  
Keyword(s):  
Human Resources ◽  
Container Terminal ◽  
Resources Allocation ◽  
Arrival Times

Assessment of establishment results of social work units among some hospitals in Vietnam for the period 2011-2020

2021 ◽  
Vol 66 (1) ◽  
pp. 118-125
Author(s):  
Nam Pham Tien
Keyword(s):  
Social Work ◽  
Human Resources ◽  
Resources Allocation ◽  
Ministry Of Health ◽  
Customer Care ◽  
Study Results ◽  
Current Context ◽  
Work Units ◽  
Initial Target

To gradually professionalize social work in hospitals, the establishment of social work units in hospitals is necessary in Vietnam's current context. The study's objective was to evaluate the establishment results of social work units among some hospitals in Vietnam for the period 2011-2020. The study was conducted from December 2019 to March 2020, with 503 hospitals, including hospitals at the central, provincial, and district levels nationwide. Our findings showed that the establishment prevalence of social work units among some hospitals was relatively high (exceeding the initial target). Human resources on social work were why some hospitals have not yet established social work units (accounting for the highest prevalence with 65.0%). The study results also showed that the larger the number of planned beds, the higher the establishment prevalence of social work units. There were four parts under social work units, including the patients’ support (59.6%), the communication (44.9%), the mobilization and resources allocation (40.8%), and the customer care (44.1%). The study also gave some suggestions to the Ministry of Health to establish social work units to be more effective in the coming time at some hospitals nationwide.

scholarly journals An attempt to optimize human resources allocation based on spatial diversity of COVID-19 cases in Poland

2020 ◽  
Author(s):  
Andrzej Jarynowski ◽  
Monika Wójta-Kempa ◽  
Łukasz Krzowski
Keyword(s):  
Human Resources ◽  
Spatial Clustering ◽  
The Elderly ◽  
Spatial Diversity ◽  
Arrival Times ◽  
Infection Dynamics ◽  
Socio Economic Variables ◽  
General Mobility ◽  
The Relationship ◽  
Second Wave

AbstractOur task is to examine the relationship between the SARS-CoV-2 arrival and the number of confirmed COVID-19 cases in the first wave (period from March 4 to May 22, 2020 (unofficial data)), and socio-economic variables at the powiat (county) level (NUTS-4) using simple statistical techniques such as data visualization, correlation analysis, spatial clustering and multiple linear regression. We showed that immigration and the logarithm of general mobility is the best predictor of SARS-CoV-2 arrival times, while emigration, industrialization and air quality explain the most of the size of the epidemic in poviats. On the other hand, infection dynamics is driven to a lesser extent by previously postulated variables such as population size and density, income or the size of the elderly population. Our analyses could support Polish authorities in preparation for the second wave of infections and optimal management of resources as we have provided a proposition of optimal distribution of human resources between poviats.

Human resources allocation in oncologic day hospital: Validation of the Kohen-Gil Deza scale (KGD) for risk assesment.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 6596-6596
Author(s):  
Nelson Kohen ◽  
Ernesto Gil Deza ◽  
Natasha Gercovich ◽  
Eduardo L. Morgenfeld ◽  
Carlos Fernando Garcia Gerardi ◽  
...  
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Human Resources ◽  
Symptom Control ◽  
Low Risk ◽  
Assessment Model ◽  
Resources Allocation ◽  
Intermediate Risk ◽  
Day Hospital ◽  
Academic Qualification

6596 Background: The oncological day hospital (ODH) at IOHM carries out 80 chemotherapies per day with 6 certified oncological nurses as staff. Human resources allocation in oncology has not been formally studied in relation to treatment risks. The objective of this paper is to present a risk assessment model for the rational allocation for human resources in the ODH using the KGD scale. Methods: The KGD scale was designed through a retrospective evaluation of more than 15,000 treatments (Tx). Between November 1st and December 1st, 2012, this instrument was validated with all new patients (Pt) beginning Tx at IOHM. The KGD scale evaluates risk according to: Five Pt characteristics (Elderly, Polymedicated, Without symptom control, Neuropsychiatric problems, Presence or absence of family members); Four Tx characteristics (New drugs, Complex protocol, High risk of acute toxicity, Infrequently used) and workplace context(New personnel, Holiday absences, With or without close medical support). The KGD scale was determined for each Tx and applied as follows: Low Risk (0-3 points): two nurses in the ODH, supervision is at the patient’s request and the chemotherapy can be administered at the beginning or end of the workday; Intermediate Risk (4-5 points): three nurses in the ODH, supervision is mandatory and the treatment can take place at any time in the workday; High Risk(6 or more points): four nurses in the ODH, supervision must be constant and the Tx must take place in the middle of the workday. The chemotherapy outcome was observed. Results: One hundred and thirty patients were admitted. Sex fem 74 (59%), male 56 (41%): age: 49y (range 22-87). Diagnosis: breast 40, colon: 21, lung: 16, ovaries:11, lymphoma: 11, testis:7, sarcoma: 5 ; others: 19 KGD risk assessment: Low Risk 25 pts (19 %); Intermediate Risk 77 pts (59%); High Risk 28 pts (21%). There were no complications in any of the 312 chemotherapy treatments administered to this cohort. Conclusions: 1) The KGD scale has shown to be a useful aid in the treatment risk assessment. 2) Use of the KGD scale allows for an efficient personnel allocation at the ODH according the Tx risk 3) The academic qualification of the nurses staff are mandatory to control the risk.

SIMULATION, ANALYSIS AND OPTIMIZATION OF CONTAINER TERMINALS PROCESSES

2012 ◽  
Vol 03 (04) ◽  
pp. 1240006 ◽  
Author(s):  
AGOSTINO BRUZZONE ◽  
FRANCESCO LONGO ◽  
LETIZIA NICOLETTI ◽  
ELEONORA BOTTANI ◽  
ROBERTO MONTANARI
Keyword(s):  
Design Of Experiments ◽  
Simulation Model ◽  
Analysis Of Variance ◽  
Simulation Analysis ◽  
Container Terminal ◽  
Service Level ◽  
Container Terminals ◽  
Arrival Times ◽  
Port Area ◽  
Freight Logistics

The freight logistics includes all the processes needed to supply industry, retailers and wholesalers and final customers with goods. Such processes generate a flow of goods that, in the global supply chain, mainly relies on the activities carried out within worldwide container terminals. In this paper, the authors present a simulation model of a real container terminal. After some preliminary analyses, the simulation model is first used with Design of Experiments and Analysis of Variance to investigate the effects of different resources allocations (i.e., number of forklifts and tractors) and some parameters (i.e., inter-arrival times, container unloading time) on the container terminal performances in terms of total number of handled containers per day. Then, based on the results achieved through the Design of Experiments and Analysis of Variance, the simulation model is used with genetic algorithms to carry out a range allocation optimization on berth assignment to incoming ships and number of tractors serving each quay crane. The aim of the optimization is the minimization of the average time spent by each ship in the port area (decreasing, as consequence, costs and increasing service level provided to final customers).

scholarly journals Agent-based Truck Appointment System for Containers Pick-up Time Negotiation

2020 ◽  
Vol 14 (1) ◽  
pp. 81
Author(s):  
Fakhri Ihsan Ramadhan ◽  
Meditya Wasesa
Keyword(s):  
Container Terminal ◽  
Time Estimation ◽  
Arrival Rate ◽  
Turnaround Time ◽  
Arrival Times ◽  
Agent Based ◽  
Appointment System ◽  
Truck Appointment System ◽  
Trucking Companies ◽  
Truck Arrival

Congestion in the seaports area is a common issue in many parts of the world. Fluctuating truck arrival has been identified as one of the significant determinants of congestion. In response, a truck appointment system (TAS) is introduced to manage truck arrival, particularly at peak times. In the existing TAS mechanism, the scheduling decision is centralized and disregards the concerns of trucking companies. Moreover, TAS may complicate the business operation of trucking companies that already have a constrained truck schedule. This study proposes a decentralized negotiation mechanism in TAS that allows trucking companies to adjust arrival times by utilizing the waiting time estimation provided by the terminal operator. We develop an agent-based model of a TAS in the container terminal pick-up procedure. The simulation results indicate that compared to the existing TAS mechanism, the negotiation TAS mechanism generates a shorter average truck turnaround time regardless of truck arrival rates. In terms of average net time cost, the negotiation TAS mechanism provides better value under high truck arrival rate conditions. The incentive for trucking companies to participate in the negotiations is even higher at peak times.

scholarly journals PEMODELAN PENJADWALAN LINIER DENGAN ALOKASI SUMBER DAYA MANUSIA PADA PROYEK PERUMAHAN

2018 ◽  
Vol 5 (2) ◽  
pp. 41-47
Author(s):  
HEDWIG ANGDIARTO TAN ◽  
Ratna Alifen
Keyword(s):  
Human Resources ◽  
Idle Time ◽  
Resources Allocation ◽  
Project Duration ◽  
Linear Scheduling ◽  
Scheduling Method ◽  
Research Findings ◽  
Working Groups ◽  
Repetitive Activities

Metode penjadwalan linier cocok untuk proyek dengan aktivitas sederhana, dan repetitif dengan jumlah unit yang tipikal, seperti proyek jalan, irigasi, tunnel, apartment, dan perumahan sederhana. Pada penelitian ini dilakukan pemodelan penjadwalan linier proyek pembangunan perumahan sebanyak 50 unit tipikal. Simulasi alokasi sumber daya manusia dan penggunaan buffer agar penggunaan sumber daya manusia dapat seefisien mungkin. Hasil penelitian diperoleh bahwa simulasi ke-8 dengan menggunakan buffer memiliki durasi 314 hari dengan 18 kelompok kerja, apabila dibandingkan dengan simulasi ke-9 tanpa menggunakan buffer memiliki durasi 180 hari dan idle time 134 hari inefisiensi 1522 orang hari.   Linear scheduling method is suitable for projects with repetitive activities, as well as tipical mass product units such as a road, apartment, and residential housings. In this research linear schedule modeling was carried out on residential typical housings project of 50 units. The simulation of linear scheduling is to minimize the idle times by using time buffers and human resources allocation so that the usage of human resources can be as efficient as possible. The research findings show that the 8th simulation by using buffers has a project duration of 314 days were chosen with 18 working groups, compares to 9th simulation without buffers that has a duration of 180 days and 134 days of idle time which with 1522 man day of inefficient.

scholarly journals An attempt to optimize human resources allocation based on spatial diversity of the first wave of COVID–19 in Poland

E-methodology ◽  
2021 ◽  
Vol 7 (7) ◽  
pp. 100-122
Author(s):  
ANDRZEJ JARYNOWSKI ◽  
MONIKA WÓJTA-KEMPA ◽  
ŁUKASZ KRZOWSKI
Keyword(s):  
Human Resources ◽  
Spatial Clustering ◽  
The Elderly ◽  
Spatial Diversity ◽  
Arrival Times ◽  
Infection Dynamics ◽  
Socio Economic Variables ◽  
General Mobility ◽  
The Relationship ◽  
Second Wave

Aim. Our task was to examine the relationship between the SARS–CoV–2 arrival and the number of confi rmed COVID–19 cases in the fi rst wave (period from March 4 to May 22, 2020 (unoffi cial data)), and socio–economic variables at the powiat (county) level.Methods. We were using simple statistical techniques such as data visualisation, correlation analysis, spatial clustering and multiple linear regression.Results. We showed that immigration and the logarithm of general mobility was the best predictor of SARS–CoV–2 arrival times, while emigration, industrialisation and air quality explain most of the size of the epidemic in poviats. On the other hand, infection dynamics is driven to a lesser extent by previously postulated variables such as population size and density, income or the size of the elderly population.Conclusions. Our analyses could support Polish authorities in preparation for the second wave of infections and optimal management of resources as we have provided a proposition of optimal distribution of human resources between poviats. Although this isa retrospective analysis of the initial phase of the epidemic, similar patterns could repeat in case of new variants of SARS–CoV–2 or new respiratory disease for immunologically naive populations.

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