Decision Making and Analysis

Simulation model of perishable item picking policies in the buffer stock of a push-pull supply chain

2024-09-04T13:42:43+08:00

This paper studies the influence of different picking policies in a stock of perishable items on the quantity of waste, the degree of freshness of the stored products and the profit. We consider a push-pull supply chain with three echelons (an agricultural producer, a manufacturer and a retailer), in which the quantity ordered from the upstream supplier is determined using a forecast based on a simple exponential smoothing of historical sales data of perishable products. To meet a stochastic demand that is symmetrically distributed around a given average, the stock of this perishable product must be sufficient without exceeding the expiration dates to avoid any waste. If the demand exceeds the available stocks, the manufacturer can resort to external suppliers on a spot market to deliver the products very quickly. We developed a simulation model to compare three picking policies (FIFO: first-in-first-out, LIFO: last-in-first-out and RDM: random picking policy) and their performance in terms of the average age of stored goods, the quantity of waste and the profit. A counterintuitive result showed that under certain conditions, the LIFO policy led to better performance than the FIFO policy, a result we proved mathematically. We then simulated different scenarios by varying product depreciation and margin rates. When margins decrease linearly with product age, the FIFO policy is the least competitive. In the case of normally distributed demand, LIFO is the most efficient picking policy, whereas in the case of uniform demand, the RDM policy performs better. We also studied the sensitivity of the model to the parameters of the demand function and the smoothing coefficients used to forecast the quantities of perishable products to be supplied. Finally, we applied our model to some specific features of the poultry and meat industry and simulated a policy of preventive production reduction.

Decision-making techniques based on aggregation operators and similarity measures under q-rung orthopair hesitant fuzzy connection numbers and their application

2024-06-25T10:44:02+08:00

The concept of q-rung orthopair hesitant fuzzy set represents an advancement and extension of hesitant fuzzy sets, encompassing both fuzzy sets and q-rung orthopair fuzzy sets. q-rung orthopair hesitant fuzzy set characterizes a set of membership and non-membership grades within the interval [0, 1], which enhances its adaptability compared to existing methods. This flexibility proves invaluable in providing more insightful data about various objects. The primary objective of this research is to introduce a decision-making technique in the context of q-RHF using the theory of set pair analysis (SPA). q-RHFS effectively handles ambiguous data by incorporating membership and non-membership grades, while the connection number (CN) based on SPA theory manages the intricacies of uncertainty and certainty structures by relying on "identity", "discrepancy" and "contrary" grades. Building on the relationship between q-RHFS and the connection number of set pair analysis, a comprehensive framework known as q-rung hesitant fuzzy connection number set (qHCNs) is developed. This model not only addresses uncertainty, but also offers valuable insights. Furthermore, this research introduces similarity measures derived from qHCN and examines their advantages through illustrative examples. Additionally, a novel approach to decision modeling utilizing these measures applied to medical diagnosis is also introduced. The application of this established model contributes to an effective approach and demonstrated its soundness and efficiency. In addition, a detailed comparative study is conducted with the existing models and advantages of proposed model. The research concludes with a summary of the authors' findings, highlighting the consistency and effectiveness of their work.

The influence of two decision-making styles on stress perception in military nursing students during clinical practice

2024-04-03T14:01:52+08:00

The primary objective of this study was to investigate how the tendency to make emotionally urgent decisions influences the perception of stressful situations in military nursing students during their clinical practice. A correlational cross-sectional design was employed, and data were collected from 79 cadets who were enrolled in a nursing program at the only Argentine military institution offering this degree. Two instruments were utilized: the Kezkak Inventory of Clinical Practice Stressors and the Inventory of Bases for Urgent Decision-Making in Extreme Circumstances. Simple linear regression analyses were conducted to assess the relationship between decision-making styles and specific stressful situations. The results indicated that the inclination to make emotionally urgent decisions was a significant predictor of overall stress perceptions and of specific situations in clinical practice, such as patient suffering, the inability to control the nurse-patient relationship, and the helplessness and uncertainty of not knowing how to proceed. This study highlighted the importance of developing emotional management skills in nursing students, particularly in military contexts, to assist them in making balanced and effective decisions in challenging clinical situations.

Telehealth use and work stress among Chinese health care providers during the COVID-19 pandemic

2023-07-07T15:01:46+08:00

Telehealth services in China rapidly expanded during the COVID-19 pandemic. The work stress of health care providers (HCPs) associated with providing telehealth care services in China has been less studied. Our study describes the telehealth services provided by hospitals in China and examines the relationships between telehealth use and work stress of HCPs in China during the COVID-19 pandemic. With a survey research design, HCPs aged 18 or older in China were electronically recruited from October 19 to November 10, 2021 (n=1,073). After preprocessing, data from 1,036 HCPs were used for further analyses, which included descriptive statistics and multiple linear regression models. Results showed that 64.29% of Chinese hospitals reported virtual physician-to-physician consultations, and 59.94% of Chinese HCPs conducted online physician consultations. Lower levels of HCP work stress was associated with live video conferencing (p=0.04), online physician consultations (p=0.00), and higher levels of team collaboration (p=0.00) and team trust (p=0.00). Work stress was also positively correlated with COVID-19 stress (p=0.00), working hours (p=0.00), and the interaction between live video conferencing and COVID-19 stress (p=0.04). HCPs’ work stress decreased by using live video conferencing and online patient care. However, the positive effects of live video conferencing may decrease with the increase in COVID-19 stress for HCPs. Our findings encourage efforts to develop extensive coverage of telehealth service systems in China to promote HCPs’ virtual communication and collaboration to relieve HCPs’ work stress and support their well-being.

Integrated and sustainable performance evaluation of urban rail transit systems using fuzzy sustainability index

2024-07-08T10:20:29+08:00

The complexity of prominent dimensions in urban rail transportation sector arises from the involvement of several stakeholders and the various interacting variables for evaluating transportation performance. This study uses a fuzzy logic-based method to present an index-based framework for sustainable performance assessment. The proposed framework presents 4 main indicators which include environmental, economic, financial and social sustainability, 14 sub-indicators, 4 main indicators for transportation system effectiveness with 13 sub-indicators and 1 main indicator for multi modal integration with 6 sub-indicators. The performance ratings and importance weights of the transport sustainability attributes are evaluated using a fuzzy logic approach. A numerical illustration is provided to demonstrate the applicability of the approach. The results show that system capacity (passenger capacity of a route), comfort and customer service (passenger environment and ride quality, maintenance cycle) and multimodal integration (park and ride facilities) were found to be weaker attributes. The proposed methodology facilitates the systematic understanding of the prominent attributes for achieving integrated and sustainable transport performance by using the ‘Fuzzy Transport Sustainability Index’.

Humanitarian logistics: A multicriteria decision approach for venezuelan refugee resettlement process

2024-06-24T11:37:31+08:00

The number of people seeking shelter in other countries is increasing due to the escalating humanitarian and political crisis. In South America, the case of Venezuelan refugees is known worldwide as the cause of local political crisis. Due to its geographic proximity to Brazil, Venezuelans tend to migrate in their primary movement to Brazilian cities that are close to the border between the two countries. Afterwards, their secondary movement is characterized by their spread throughout the Brazilian territory, also known as resettlement. In this sense, this paper aims to propose a multicriteria decision making approach for choosing the best cities as resettlement locations for the Venezuelan refugees in Brazil. The study was conducted considering fifteen cities in the state of Amazonas. The multicriteria decision making methods Best-Worst Method (BWM) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were applied. The BWM method focused on determining the weights of the decision criteria, while the TOPSIS method was instantiated to rank the decision alternatives. The decision criteria that are associated with employment and basic sanitation were given the highest weights, as they represent the most important needs of the refugees. The analysis of the decision alternatives showed that the city of Manaus, Humaitá and Iranduba were the top three in the alternatives ranking. Although these alternatives have different characteristics reflected in their performance regarding the decision criteria, they are recommended as resettlement locations because they can satisfy the most important needs of the refugees.

Real-time monitoring and diagnostics of the person's emotional state and decision-making in extreme situations for healthcare

2023-10-27T17:01:16+08:00

Monitoring and diagnosing the emotional state is important for varied professional groups, especially, those involve in hazardous work, risks, and high responsibility (pilots, astronauts, miners, sailors, firefighters, military personnel, law enforcement officers, etc.). These professions are definitely extreme. Moreover, the number of these professions and people engaged in them is constantly increasing. Unfortunately, disorders of the emotional state are not easily recognized by visible symptoms, so prompt remote diagnosis and monitoring of a person's emotional state is important, especially in conditions of complex geography, lack of transportation and mobility of patients, reduced financial resources, or lack of medical staff. In many cases, effective supports from various participants involved in a difficult situation that could become dangerous are required to make a timely decision. The authors, who have aviation experience in operational detection of deviations in the pilot's emotional state and decision making under risk, propose to apply the concept of mental activity, which is based on the property of the mind to slow down or speed up the flow of subjective time in relation to the real one, for the monitoring and diagnosing the emotional state of a person. For the timely detection of a hazardous emotional state of a person in an extreme situation, the phase plane method is used, the essence of which is to build phase trajectories for differential equations in the coordinate system. The identification of a person's emotional state in real time is based on the variance analysis of the models of spontaneous (optimal), emotional and rational activities. The deformity of the emotional state is determined using a priori person’s models based on the actual material of a posteriori research of the accident investigations. The Nyquist criterion is used to measure the functional stability of a person. The method of real-time diagnostics of the person’s emotional state is presented. A software “Diagnostics of the emotional state of a human-operator” is developed.

The problem of effective monitoring and diagnostics of a person's emotional state can be solved with the help of an Intelligent Remote Monitoring System (IRMS) built on the basis of dynamic modeling principles, when the subsystems are formalized in the form of transfer functions. A person is considered as a control object, and the monitoring and diagnostics of the emotional state are based on the analysis of the phase portrait obtained by the control device. The conceptual model and the functional diagram of medical IRMS are worked out. The algorithm for monitoring and diagnosing the person’s emotional state is presented. Mikhailov and Nyquist criteria are used to determine the IRMS stability; Mikhailov and Nyquist hodographs are built. IRMS is proposed for monitoring the emotional state of a person in medicine, sports, treatment, and for automated monitoring of persons in hazardous environments, for example, in an aeroplane (passengers), in a smart home (people), in medicine (patients), etc. Prompt monitoring and diagnosis enables timely adjustment and improvement of a person's emotional state and prevents the development of an extreme situation towards worsening.

Based on the objective-subjective collaborative decision-making method under uncertainty, the problem of urgent delivery of medical cargo using UAV from the point of departure to the destination is solved. The optimal decision with minimum risk and maximum safety according to the Wald-Wald, Wald-Laplace, and Wald-Hurwitz criteria and with the consideration of all participants’ opinions on UAV transportation, is found. Based on the dynamic programming method, the task of finding a route with minimum cost is solved when it is necessary to urgently deliver medicines to a seriously ill patient using UAV.