Modeling, analysis, and design of supply chain networks with the integration of nonlinear Cost of Quality Functions

Due to the complexity of the supply chain, sourcing and distribution activities within the supply chain require a fair deal of orchestrating in order to eliminate delays and other inefficiencies. For this reason, researchers have worked effortlessly to incorporate a wide range of parameters in the modeling of the supply chain. The parameters integrated have touched many important issues. As important, issues pertaining to quality are of great importance in organizations. Some literature has discussed quality from the perspective of the supply chain and acknowledged the lack of a consistent vision pertaining to quality throughout the supply chain. With many industries today on the quest of improving their quality systems, finding ways to reduce nonconformities and failure of products is crucial. In industries such as the aerospace industry, the variable production cost is considerably high; hence producing extra parts to compensate for defectives would be a costly option. While Cost of Quality (COQ) is a very good indicator of how much poor quality is costing a company, the literature lacks a work that aims at integrating COQ into Supply Chain Network Design (SCND). This thesis aims at exploring the challenges in doing so and introduces a comprehensive supply chain model that minimizes a series of costs, in which COQ is integrated. The inclusion of COQ is done through the integration of quadratic quality function. The overall supply chain is mathematically modeled producing a nonlinearity in the objective function and in the constraints. Hence this thesis solves a constrained binary nonlinear programming problem. Further, this work integrates binary entities, to allow for assignable/set-up costs, into the model and introduces seven solution procedures to solve the model. A real life supply chain network is used to extract relevant results. The real life supply chain is in the domain of the aerospace industry and has an n level Bill of Material (BOM). Heuristics have been introduced to solve Binary Quadratic Programming (BQP) problems before. A majority of these heuristics are geared towards unconstrained problems where feasibility might not be a concern. Alternatively in the COQ model, constraints bind the objective function making feasibility a criterion for optimality. Therefore, the seven solution procedures entertain a feasibility check mechanism and one of the seven solution procedures is a hybrid solution procedure formulated to tailor for the special topography of the feasible solution region of the proble

Investigation of the effective factors on branding in cosmetic and hygienic products (Case study: Ladies consuming cosmetic and hygienic products with local brands)

Despite the long history of brands, this concept has been considered in marketing literature for a long time such that it has attracted many experts' attention to this field as one of the most important concepts of modern marketing literature. This concept has become so important that wherever loyalty is mentioned, brand is undoubtedly considered too. This research aims to investigate the effect of marketing mixture (7Ps) on making brands of local hygienic and cosmetic products whose statistical society is ladies consuming hygienic and cosmetic products in Mashhad. The sample under analysis of this research consists of 381 people. It was identified after the analysis of their data using SPSS software and testing the research's assumptions that marketing mixture's factors are effective on making brands. In addition, the severity of the effect of each factor was identified

Investigation of the effective factors on branding in cosmetic and hygienic products (Case study: Ladies consuming cosmetic and hygienic products with local brands)

Despite the long history of brands, this concept has been considered in marketing literature for a long time such that it has attracted many experts' attention to this field as one of the most important concepts of modern marketing literature. This concept has become so important that wherever loyalty is mentioned, brand is undoubtedly considered too. This research aims to investigate the effect of marketing mixture (7Ps) on making brands of local hygienic and cosmetic products whose statistical society is ladies consuming hygienic and cosmetic products in Mashhad. The sample under analysis of this research consists of 381 people. It was identified after the analysis of their data using SPSS software and testing the research's assumptions that marketing mixture's factors are effective on making brands. In addition, the severity of the effect of each factor was identified

A solution method for a two-layer sustainable supply chain distribution model

This article presents an effective solution method for a two-layer, NP-hard sustainable supply chain distribution model. A DoE-guided MOGA-II optimiser based solution method is proposed for locating a set of non-dominated solutions distributed along the Pareto frontier. The solution method allows decision-makers to prioritise the realistic solutions, while focusing on alternate transportation scenarios. The solution method has been implemented for the case of an Irish dairy processing industry׳s two-layer supply chain network. The DoE generates 6100 real feasible solutions after 100 generations of the MOGA-II optimiser which are then refined using statistical experimentation. As the decision-maker is presented with a choice of several distribution routes on the demand side of the two-layer network, TOPSIS is applied to rank the set of non-dominated solutions thus facilitating the selection of the best sustainable distribution route. The solution method characterises the Pareto solutions from disparate scenarios through numerical and statistical experimentations. A set of realistic routes from plants to consumers is derived and mapped which minimises total CO2 emissions and costs where it can be seen that the solution method outperforms existing solution methods

Understanding the risk and protective factors associated with obesity amongst Libyan adults - a qualitative study

BACKGROUND: There are a range of multifaceted behavioural and societal factors that combine to contribute to the causes of obesity. However, it is not yet known how particularly countries' cultural norms are contributing to the global obesity epidemic. Despite obesity reaching epidemic proportions in Libya, since the discovery of oil in 1959, there is a lack of information about obesity in Libyan adults. This study sought to explore the views of key informants about the risk and protective factors associated with obesity among Libyan men and women. METHODS: A series of qualitative semi-structured interviews were conducted with Libyan healthcare professionals and community leaders. RESULTS: Eleven main themes (risk and protective factors) were identified, specifically: socio-demographic and biological factors, socioeconomic status, unhealthy eating behaviours, knowledge about obesity, social-cultural influences, Libya's healthcare facilities, physical activity and the effect of the neighbourhood environment, sedentary behaviour, Libyan food-subsidy policy, and suggestions for preventing and controlling obesity. CONCLUSIONS: Key recommendations are that an electronic health information system needs to be implemented and awareness about obesity and its causes and consequences needs to be raised among the public in order to dispel the many myths and misconceptions held by Libyans about obesity. The current political instability within Libya is contributing to a less-active lifestyle for the population due to security concerns and the impact of curfews. Our findings have implications for Libyan health policy and highlight the urgent need for action towards mitigating against the obesity epidemic in Libya

Forecasting and optimization stock predictions: Varying asset profile, time window, and hyperparameter factors

Machine learning has made significant progress in various fields, including financial markets. Numerous studies have applied different machine learning algorithms to predict stock market behavior, but these studies often face challenges in terms of data acquisition and preparation, algorithm design, hyperparameter optimization, and feature selection, as well as the inherent volatility of stocks. In this work, our aim is to review the literature for comprehensive studies that address these challenges and enhance the state-of-the-art by introducing novel factors, such as multi-time windows, training batch size, stopping criteria, training data ratio, and financial technical indicators. We observe statistical significance when varying the training period window, with a p-value lower than 0.0001. However, genetic-based hyperparameter optimization brings about a significant 40% improvement compared to random-grid search. Concerning the inclusion of technical indicators, we see little improvement in terms of prediction accuracy, but there is some improvement in directional prediction accuracy across several stocks. Overall, the results show high variation with respect to the time window chosen for conducting a study. Additionally, we discover that the characteristics of the stock and the time period, including the length of the time period and the specific start and end dates, significantly impact prediction accuracy

Effect of Patients\u27 Awareness of CVD Risk Factors on Health-Related Behaviors

OBJECTIVES: In 2010, the American Heart Association unveiled a strategic plan to reduce cardiovascular deaths by targeting seven components of ideal cardiovascular health. Although education is a sensible first step, it is not known whether awareness correlates with healthy behavior. The objective of the study was to examine the association between awareness of risk factors and ideal cardiovascular health behavior. METHODS: We surveyed patients 40 years and older at five ambulatory clinics. The survey measured demographics, health management behaviors, comorbidities, and awareness of five modifiable cardiac risk factors (smoking, obesity, high cholesterol, hypertension and diabetes mellitus) and one protective factor (exercise). Healthy behavior was defined as follows: diabetes, hemoglobin A1c RESULTS: For five modifiable risk factors, awareness was positively associated with healthy behavior in multivariable models: obesity, hypertension, exercise, cholesterol, and diabetes. Awareness was inversely associated with smoking abstention. CONCLUSIONS: Awareness that a specific factor increases the risk for cardiovascular disease was positively associated with healthy behavior regarding most risk factors; however, the association was modest, suggesting that awareness alone does not motivate behavior