Michel Fathi

• PhD
• Professor (Assistant) at University of North Texas

This paper introduces the Theory of AI-driven scheduling (TAIS), an innovative framework designed to revolutionize service-oriented scheduling by integrating the theory of constraints (TOC) (see APPENDIX I) with cutting-edge Artificial Intelligence (AI) technologies. TAIS extends the traditional five steps of TOC by introducing three additional lay...

Manufacturing operations rely heavily on external sources and supply chain (SC) networks, making them susceptible to material and operational risks. In response, manufacturers are investigating innovative strategies to enhance their adaptability and strengthen the resilience and viability of their value-creation systems. This shift has prompted an...

Airports are increasing their capacity to accelerate and facilitate travel and cargo delivery. At the same time, they aim to decrease expenses on delays caused by capacity overflow, encouraging policymakers to plan to enhance the capacity of crowded airports for the long term and set their transportation policies accordingly. This study develops a...

Transportation services play a critical role in our daily lives, facilitating the movement of people and goods between different locations. The issue of voluntary driver turnover has been examined in this study. Leveraging a dataset from an intercity bus company, over 30 variables have been examined to uncover patterns and pivotal factors that impa...

Supply chain (SC) resiliency and risk management have garnered increasing attention recently. While several studies have explored the use of scale-free network models to design and optimise SC networks, there remains a lack of a generalised stress-testing method that can be applied to various types and sizes of SCs. To address this, we propose a no...

Several developed vehicle spaces and time headway distribution models in traffic flow theory have been widely used in the literature, reflecting the primary uncertainty in drivers’ car-following movements and explaining the traffic flow stochastic features. Moreover, effective vehicle-to-vehicle (V2V) communication is a key to decentralizing traffi...

Infrastructures such as power stations, water systems, railways, highways, subway stations, and roads play an important role in ensuring that the network operates safely and effectively. In this study, we aim to develop a fortification plan to protect the nodes and links from destructive attacks. However, there is often a degree of uncertainty conc...

The literature on fatigue analysis can be classified into parametric or analytic approaches that try to model the fatigue data with a specific distribution, such as the optimal sequential Accelerated Life Test (ALT), considering the fatigue life cycle and stress amplitude. To the best of our knowledge, no work incorporates the accel- erated lifecyc...

This study configures various carbon regulation mechanisms to control carbon emissions following clean technology strategies in engine oil production. Considering clean technology strategies for designing a sustainable supply chain (SSC) in the engine oil industry, two carbon reduction policies, namely, carbon capacity and carbon emissions tax, are...

The optimal operation of a conveyor network used in distribution centers is critical to delivery service quality. Optimizing conveyor operations entails routing a given number of items from loading locations to unloading locations in the shortest possible time, called makespan. Developing an efficient model for conveyor operations is necessary to a...

In Reliability Redundancy Allocation Problem (RRAP), the reliability and redundancy of components in a given system configuration are determined while concerning some problem-specific constraints. RRAP can be applied to various industries. Moreover, queueing systems are among the most common systems in the manufacturing and service industries. Fail...

Product return policies are widely utilized to increase customer security in retail markets. As a result, many retailers take various return leniency measures to ease the applicability of product returns for customers, which increases the frequency of returns in the market and has huge economic impacts on retailers. Therefore, it is necessary to ac...

This research is motivated by a scheduling problem arising in the ion implantation process of wafer fabrication. The ion implementation scheduling problem is modeled as an unrelated parallel machine scheduling (UPMS) problem with sequence-dependent setup times that are subject to job release time and expiration time of allowing a job to be processe...

This paper reports an integrated model for evaluating an early-stage third-party mobile application developer. By combining qualitative analyses, including Business Model Canvas (BMC), strengths, weaknesses, opportunities, threats analysis, and scenario planning, as well as quantitative analysis based on financial modeling and valuation, this study...

In United States (U.S.), government-funded organizations, such as NLDAC, reimburse travel and subsistence expenses incurred during living-organ donation process. However, in Iran, there is a non-governmental organization called Iranian Kidney Foundation (IKF) that funds the direct and indirect costs of donors through charitable donations and contri...

In this special issue, we call for rigorous research that borrows from various disciplines and presents relevant and original work related to the disruption of illicit markets using OR and analytics approaches. This can be rendered in various forms, such as a new way of framing the issue via problematization, design approaches and constraint induce...

The goal of this special issue is thus to improve the research and practice in issues related to analytics AI and OR solutions for social goods (AI&OR4SG) by mutually benefit from practitioners, researchers, and policymakers international collaborations; promoting the development of new methodology and metrics to address the specific challenges rel...

The reliability of products can be affected by the quality errors which may occur during the production process. Product reliability decreases when the rate of manufactured products with quality errors increases. Detecting the quality errors and monitoring their rate can be essential in monitoring the reliability of products. In this research, a Be...

In recent years, the Public Bicycle Sharing System (PBSS) popularity for urban transportation is increasing. The fleet size of the system and the capacity of its stations are some key factors in establishing a successful sharing system. These factors affect the number of rejected demands and the lack of free docks for returning bicycles because of...

With the data in the world approximating 64.2 zettabytes in 2020 and is projected to hit 180 zettabytes by 2025 [1], Data analytic has evolved overtime to be the backbone for any sector to generate valuable insights and make confident decisions. It has four main branches ranging from descriptive-analytic, diagnostic analytics, predictive analytics,...

We consider a location-inventory optimization model for supply chain (SC) configuration. It includes a supplier, multiple distribution centers (DCs), and multiple retailers. Customer demand and replenishment lead time are considered to be stochastic. Two classes of customer orders, priority and ordinary, are assumed based on their demand. The goal...

Society 5.0 refers to an advanced society based on big data, artificial intelligence, sensors, and robots to improve many aspects of life in a smart city. The role of sensors in Society 5.0 is critical. Sensors and the Internet of Things can be considered to work as a service system. Specifically, sensors can track millions of objects to support ci...

In clinical psychology, reinforcement learning is one of the many forms of conditional learning that focuses on reinforcing behavior that yields beneficial results. Similar to any other structure, the process of reinforcement learning was adopted and implemented into models of machine learning with ever-evolving complexity. This chapter attempts to...

Medication Errors (MEs) are still significant challenges, especially in nonautomated health systems. Qualitative studies are mostly used to identify the parameters involved in MEs. Failing to provide accurate information in expert-based decisions can provoke unrealistic results and inappropriate corrective actions eventually. However, mostly, some...

Advanced insurance companies move toward using advanced technologies such as telemat-ics to develop fair and transparent pay-as-you-drive (PAYD) automobile insurances. The expert service providers' opinions are essential and valuable for them to avoid and control any risk of entering a new market. Therefore, this study explores the critical factors...

The upsurge in atmospheric CO2 levels has come to humankind’s attention during the last couple of decades, mainly because the global temperature has risen, ice sheets have melted, and natural disasters have been happening more frequently and with more intensity. Hereby, the focus of this study is to develop a robust routing model that minimizes CO2...

This work introduces a formation and variety of decision-making models based on operations research modeling and optimization techniques in smart manufacturing environments. Unlike traditional manufacturing, the goal of Smart manufacturing is to optimizing concept generation, production, and product transaction and enable flexibility in physical pr...

Ambient Intelligence (AmI) is built using sensors and actuators connected through real-time networks for smart systems. The data and signals captured from sensors are ambiguous for both human and machine. Artificial Intelligence (AI) is merged into an ambient environment to translate data and signals into a language understandable by human users an...

The upsurge in atmospheric CO2 levels has come to humankind's attention during the last couple of decades, mainly because of the rise in the global temperature, ice sheets melting, and more frequent and intense natural disasters. Hereby, the focus of this study is to develop a robust routing model that minimizes CO2 transportation emissions so that...

In this paper, we formulate an optimization-hedging model which demonstrates how Operational Research methods and analytics can take advantage of big data sources to inform business decisions in the renewable energy sector. This is achieved by incorporating an analytical technique called Co-cluster (Copula Clustering) Algorithm in measuring risks c...

The main objective of this study is to investigate the relationship between the COVID-19 and the weather factors of the most populated and industrialized countries in Europe and propose the best mathematical model to forecast the daily number of COVID-19 cases. To find the relationship between the COVID-19 and the weather factors of absolute humidi...

Traditional defect classification of TFT-LCD array processing leaned on human decision-maker in which visual inspection used to categorize defects and consequently identify the rout-causes of defects. In practice, the main sources of defects in the TFT-LCD array process are particles. Due to the huge size of the machinery and production tools in th...

Purpose-This study aims to explore the forthcoming trend of MS industry by examining its business model canvas and describing the business functions and role of the players in this industry. Design/methodology/approach-In order to discover the potential market, other than mining the academic paper, an in-depth interview method is implemented to gat...

The properties of a learning-based system are particularly relevant to the process study of the unknown behavior of a system or environment. In the semiconductor industry, there is regularly a partially observable system in which the entire state of the process is not directly or fully visible due to uncertainties or disturbances. The model for stu...

Scheduling under nonrenewable resources is one of the challenging issues in project scheduling problems. There are many cases where the projects are subject to some nonrenewable resources. In most of the literature, nonrenewable resources are assumed to be available in full amount at the beginning of the project. However, in practice, it is prevale...

This study concerns small and medium-sized enterprise (SME) suppliers suffering from cash constraints in operations, money shortages with possible disruptions and cost uncertainty because of the distributor’s supply risk and the information asymmetry. Thus, this study adopts the distributor’s (buyer’s) perspective and applies a credit guarantee mec...

The amount of time patients spends on services to be delivered in clinics, still is a major problem of some health centers. To solve this problem, various methods proposed by researchers. Failure Mode and Effects Analysis (FMEA) is one of the most used approaches to identify influential failure modes in prolongation of waiting time. In the FMEA met...

Q&A with students and faculties of Mississippi State University

This study aims to develop a minimax game model for control design of overlay errors for semiconductor manufacturing. We highlight the main challenge in the control system of high-mixed wafer fabrication called overlay control. Indeed, the sophisticated and high-mixed setting is generated by multiple recipe adjustments for the scanner. The complexi...

Semiconductor manufacturing is a capital-intensive industry, in which matching the demand and capacity is the most important and challenging decision due to the long lead time for capacity expansion and shortening product life cycles of various demands. Most of the previous works focused on capacity investment strategy or product-mix planning based...

Abstract. There are many challenges in healthcare which can be solved by AI, operations research and data science techniques. We discuss the role of optimization and AI in Large Scale Problems with applications in Industry 4.0 and Society 5.0 and more examples in health 4.0. The tracking of patient orders in health 4.0 supply chain is a critical pr...

This presentation provides inventive thinking and insightful management solutions to the many challenges that decision-makers face in their predictions, preparations, and implementations of the key elements that our societies and industries require to take as they move toward digitalization and smartness. We want to uncover the sources of large-sca...

Abstract. There are many challenges in healthcare which can be solved by operations research and data science techniques. We discuss the role of optimization in Large Scale Problems with applications in Industry 4.0 and Society 5.0 and more examples in health 4.0. The tracking of patient orders in health 4.0 supply chain is a critical problem. We c...

— It is vital to have an exclusive modification in semiconductor production process because of meeting differentiated customer demands in dynamic and competitive global minuscule semiconductor technology market and the highly complex fabrication process. In this paper, we propose a control system based on the dynamic mixed-effect least-square suppo...

This chapter introduces a framework of disturbance rejection controller for discrete-time Run-to-Run (R2R) control system in semiconductor manufacturing environments. While we discussed the source of uncertainty and disturbance in wafer fabrication process, the photolithography process as one of the cutting-edge steps in wafer fabrication is select...

With advances in information and telecommunication technologies and data-enabled decision making, smart manufacturing can be an essential component of sustainable development. In the era of the smart world, semiconductor industry is one of the few global industries that are in a growth mode to smartness, due to worldwide demand. The important oppor...

The performance of reliability inference strongly depends on the modeling of the product’s lifetime distribution. Many products have complex lifetime distributions whose optimal settings are not easily found. Practitioners prefer to utilize simpler lifetime distribution to facilitate the data modeling process while knowing the true distribution. Th...

Advanced insurance companies are willing to use telematics to develop fair and transparent pay-as-you-drive (PAYD) automobile insurances. In Taiwan, the opinions of the expert service providers are essential and valuable for them to avoid and control any risk of entering the market. Therefore, this study aims to explore the key factors for introduc...

This volume provides resourceful thinking and insightful management solutions to the many challenges that decision makers face in their predictions, preparations, and implementations of the key elements that our societies and industries need to take as they move toward digitalization and smartness. The discussions within the book aim to uncover the...

Ambient Intelligence (AmI) refers to a networked environment of computing devices for implementing a "smart" system. AmI is built using sensors and actuators connected through real-time networks. The data and signals captured from sensors are ambiguous for both human and machine. Artificial Intelligence (AI) is merged into an ambient environment to...

Operations research and optimization in healthcare and disease modeling have received significant attention in the last three decades. This paper surveys several perspectives of operations research techniques in kidney disease, such as graph theory, queueing theory, Markov chain, and Phase-Type distribution (PTD). The kidney related problems includ...

The goal of this study is to recognize various factors for responsive SCs that affect supply risk and model their impact on SC design and operation. We propose a conceptual model for SC responsiveness that encompasses practices such as flexibility, agility, internal integration, and visibility. This conceptual model is utilized to build up a multi-...

In this book, theory of large scale optimization is introduced with case studies of real world problems and applications of structured mathematical modeling. The large scale optimization methods are represented by various theories such as Benders’ decomposition, logic-based Benders’ decomposition, Lagrangian relaxation, Dantzig –Wolfe decomposition...

In this work, a mixed-integer binary non-linear two-echelon inventory problem is formulated for a vendor-buyer supply chain network in which lead times are constant and the demands of buyers follow a normal distribution. The problem being formulated is a combination of an (r, Q) and periodic review policies based on which an order of size Q is plac...

Environmental issues like water, energy, and waste are necessitated organizations to understand that they are part of a more extensive system and their system needs to be radically transformed to respect to the society and guarantee the future of their business. More meticulously, the environmental issues would shape the future of the business. The...

The redundancy allocation problem is an important problem in system reliability design. Many researchers have investigated the redundancy allocation problem under different assumptions and for various system configurations. However, most of the studies have disregarded the dependence among components and subsystems. In real-world applications, the...

Presentation file: https://prezi.com/view/7DNvfZgJveyCbicduTJv/

The team orienteering problem with time windows (TOPTW) is a well-known variant of the orienteering problem (OP) originated from the sports game of orienteering. Since the TOPTW has many applications in the real world such as disaster relief routing and home fuel delivery, it has been studied extensively. In the classical TOPTW, only one profit is...

Non-convex optimization can be found in several smart manufacturing systems. This paper presents a short review on global optimization (GO) methods. We examine decomposition techniques and classify GO problems on the basis of objective function representation and decomposition techniques. We then explain Kolmogorov’s superposition and its applicati...

A post-industrial revolution is encouraging the deployment of novel concepts both for designing smart factories and for creating a new generation of monitoring, control and man-machine collaboration systems. In general, companies are embracing an era of smart manufacturing built upon Cyber Physical Systems (CPS), the Internet of Things (IoT), and C...

Manufacturing in developed nations must incorporate more data capture and decision support to control costs and maintain product quality. Digital transformation of manufacturing means production must be transformed using technologies like robotics, Internet of Things (IoT), Intelligent systems, and real-time analytics. Smart manufacturing means all...

With advances in information and telecommunication technologies and data-enabled decision-making, smart manufacturing can be an essential component of sustainable development. In the era of the smart world, semiconductor industry is one of the few global industries that are in a growth mode to smartness, due to worldwide demand. The promising signi...

Kidney disease is the 9TH leading cause of death in the United States. An estimated \textbf{31 million people} in the United States (10\% of the adult population) have chronic kidney disease (CKD). \textbf{9 out of 10} people who have stage 3 CKD (moderately decreased kidney function) do not know it. CKD is more common among women, but \textbf{men...

The advent of high throughput technologies such as next generation sequencing has produced vast datasets and fundamentally changed the landscape of clinical bioinformatics and translational medicine. With these huge, wide spread “omics” and clinical data available, it is becoming more and more practical to help doctors in clinical diagnostics and c...

Shrinkage in semiconductor devices affects the process window of all wafer fabrication steps including plasma etching. Drifts or shifts are most significant effects on the etching process due to shrinkage in semiconductor devices. Any drift or shift affects on critical dimensions (CD) of the wafer and changes the thickness and the width over time....

This study is dedicated to Order Penetration Point (OPP) strategic decision making which is the boundary between Make-To-Order (MTO) and Make-To-Stock (MTS) policies. This paper considers two competing supply chains in which a manufacturer produces semi-finished items on a MTS basis for a retailer that will customize the items on a MTO basis. The t...

We develop an optimization model for a supply chain, integrating both location and inventory decision making. The supply chain consists of one supplier, multiple distribution centers and multiple retailers, and is subject to stochastic customer demand and supply lead times. The objective is to simultaneously optimize the locations of distribution c...

We consider a remanufacturing system with two streams of returned products and different variability levels (high and low). The arrival of returns with high variability is modeled with a hyperexponential renewal process and that of returns with low variability is modeled with a Poisson process. The remanufacturing facility can process the returned...

We consider a remanufacturing system with two streams of returned products and different variability levels (high and low). The arrival of returns with high variability is modeled with a hyperexponential renewal process and that of returns with low variability is modeled with a Poisson process. The remanufacturing facility can process the returned...

This study is dedicated to strategic decision-making regarding order penetration point (OPP), which is the boundary between make-to-order (MTO) and make-to-stock (MTS) policies. This paper considers a supply chain in which a manufacturer produces semi-finished items on an MTS basis for a retailer that will customise the items based on MTO policy. T...

This paper analyzes a two-facility location problem under demand uncertainty. The maximum server for the ith facility is It is assumed that primary service demand arrivals for the ith facility follow a Poisson process. Each customer chooses one of the facilities with a probability which depends on his or her distance to each facility. The service t...

This study is dedicated to order penetration point (OPP) strategic decision making which is the boundary between make-to-order (MTO) and make-to-stock (MTS) policies. A multiproduct multiechelon production supply chain is considered where the first production stage manufactures semifinished products based on an MTS policy to supply the second produ...

Speed and price are the two most important factors in customer satisfaction and business success in today’s competitive environment. Time-based product differentiation and segment pricing have provided firms with a great opportunity to profit enhancement. This paper presents a coding system for pricing/queuing models in the literature. In this arti...

This research has modelled a queuing system with no standard states. In order to analyse these systems, some parameters such as the mean of waiting time and the length of queue are computed. These situations usually occur when there is delay in the service, for example, in the gas queuing system that cars are unable to leave after receiving the req...

Despite the fact that control charts are able to trigger a signal when a process has changed, it does not indicate when the process change has begun. The time difference between the changing point and a signal of a control chart could cause confusions on the sources of the problems. Knowing the exact time of a process change would help to reduce th...

The distribution center location problem is a crucial question for logistics decision makers. The optimization of these decisions needs careful attention to the fixed facility costs, inventory costs, transportation costs and customer responsiveness. In this paper we study the location selection of a distribution center which satisfies demands with...

This paper analyzes a two-facility location problem under demand uncertainty. The maximum server for the ith facility is M i ( i= 1 2). It is assumed that primary service demand arrivals for the ith facility follow a Poisson process. Each customer chooses one of the facilities with a probability which depends on his or her distance to each facility...

F Fu uz zz zy y Q Qu ue eu ui in ng g A Ap pp pr ro oa ac ch h f fo or r D De es si ig gn ni in ng g M Mu ul lt ti i S Su up pp pl li ie er r S Sy ys st te em ms s ((C Ca as se e: : S SA AP PC CO O C Co om mp pa an ny y)) K KE EY YW WO OR RD DS S ABSTRACT The importance of reliable supply is increasing with supply chain network extension and just-i...

The importance of reliable supply is increasing with supply chain network extension and just-in-time (JIT) production. Just in time implications motivate manufacturers towards single sourclng, which often involves problems with unreliable suppliers. If a single and reliable vendor is not available, manufacturer can split the order among the vendors...

We consider a supply chain that includes a manufacture which produces more than one product that are demanded by several retailers. After production, each all type of products is hold in separated warehouses. Each warehouse has different holding cost and each product has a different backorder cost. We formulate a linear cost function to aggregate a...

In this paper, we apply queuing models for performance evaluation analysis in multi-product multi-echelon manufacturing supply chain network with batch ordering. The analysis is clubbed with an inventory optimization model, which can be used for designing inventory policies for each product. We consider a three-echelon supply chain: retailers, ware...