Course Description: Fundamental optimization tools for quantitative analysis to develop modeling and decision-making skills in management sciences; Linear programming; Integer programming; Nonlinear programming; Goal programming; Game theory; Markov chains; Queuing theory and decision analysis techniques; Advanced topics in optimization. 

Course Description: Principles of domestic and international logistics and supply chain systems; Smart logistics; Smart transportation, production planning, inventory control, purchasing and procurement, packaging, supply chain integration; Information technologies and management of information system/development and analysis, model-based, data-based and knowledge-based systems and knowledge engineering; New emerging technologies in smart logistics such as e-logistics and supply chain, Big data and Internet of Thing (IOT), radio frequency identification (RFID); Green logistics; Smart global supply chain models; International transportation and risk analysis; Government regulations and intervention. 

Course Description: Design, analysis, and implementation of enterprise-wide resource and production planning and control systems; Demand forecasting, aggregate planning; Decision support models for production planning; Master scheduling; Shop floor control; Inventory control and policy; Maintenance and reliability in engineering systems; Applications of information technologies such as ERP and MRPII to production and operations planning and control.

Course Description: Quantitative and qualitative methods of data collection and data analysis, research question design, planning of research process, techniques and tools for data collection, analysis and validation of research data. Topics to enhance students’ written and spoken English skills to effectively communicate research ideas and results related to their specific disciplines. Research ethics, technical publication preparation, journal databases, publication ethics, and plagiarism checking.

Course Description: Understanding the role of modeling and simulation in the development and improvement of logistics and supply chain operations; Methodology and modeling; Conducting of a simulation study; Hands-on exercise of a particular software package and its application in a practical context.

Course Description: Overview of the procurement and purchasing activities in a supply chain; Supplier evaluation and selection; Pricing, negotiation, contracts; Outsourcing; Multiple sourcing; Just-in-time procurement; Inventory management; Buying decisions and plans; Cost analysis; Purchase agreements; E-procurement; Real-time internet-based e-supply chains; Reverse logistics and customer services; Supply chain for financing; Purchasing analysis of capital equipment; Institutional and government purchases.

Course Description: Characteristics of various modes of domestic and international transportations; Vehicle types; Urban, air, ocean, highway, pick-up and delivery systems; Scheduling; Factors that influence transport demand; Costs; Market structures; Carrier pricing; Carrier operating and service characteristics and their influence on other supply chain costs and supply chain performance, such as routes, labor, competition.

Course Description: Fundamental operations in warehousing including roles of warehousing, layout and facility design, warehouse technology such as bar codes, radio frequency identification (RFID) for inventory control systems, modern warehouse operations, classifying products, materials handling, racking and shelving, automated storage and retrieval systems (AS/RS), aisle width decision; Information technology for warehouse operations; Health and safety issues.

Course Description: Fundamental of Design of Experiment; Simple experiment design, factorial, fractional factorial experiments; ANOVA analysis, model adequacy analysis, mixed level designs, response surface methodology and Taguchi design; Review of successful experimentation in Supply Chain Management practices.

Course Description: Profitability, liquidity; Analysis and interpretation of published financial statements; Cost behavior analysis; Profit, volume analyses; Budget preparation and control; Standard costing; Divisional, segmental performance measurement; Capital investment; Risk and uncertainty analysis; Effects of inflation and taxation; Introduction to computer based financial modeling; Good corporate governance.

Course Description: Logistics case study analysis to develop master students’ problem solving skill; Applying analytical tools, quantitative and/or qualitative tools, and mathematical and/or simulation models to analyze logistics problems; Real problems from industry and research articles with supporting data in transportation management, inventory management, distribution network design, and other logistics, supply chain related problems; Visits to industrial sites, factories, distribution centers to learn problem context and for data collection.

Course Description: Introduction to physical network design modelling; Advanced modelling techniques and their application in network design and logistics; Emerging trends in supply chain network operations and the impact on their design.

Course Description: Advanced topics in integrated logistics and supply chain operations which are not offered in other Logistics and Supply Chain Systems courses. Topics may vary from semester to semester.

Course Description: Advanced topics in integrated logistics and supply chain operations which are not offered in other Logistics and Supply Chain Systems courses. Topics may vary from semester to semester, but are different from SE630.

Course Description: A study on current interests in the field of logistics and supply chain systems and operations.

Course Description: A study on current interests in the field of logistics and supply chain systems and operations that are different from SE632.

Course Description: Concepts, tools and techniques of artificial intelligence (AI); data science; machine learnings; decision tree, artificial neural network, support vector machine, ensemble method, convolutional neural network, and deep learning; standard process of data mining; RapidMiner Studio; Google COLAB; data-driven decisions; AI prototype development; best practices; case studies.

Course Description: Concepts, tools and techniques of business intelligence; data visualization; data exploration; business analytics in descriptive, predictive, and prescriptive; data cleansing, verification, validation, and integration; data mining; data-driven business decisions; design of analytics dashboard prototype; best practices and case studies.

Course Description: Students will conduct research studies in the area of logistics and supply chain systems engineering or services science and engineering under the supervision of their thesis advisor. Research areas include production logistics analysis (production planning, inventory control, maintenance, reliability, scheduling specifically for and limited to logistics and supply chain systems), procurement logistics analysis (e-procurement, outsourcing, multiple sourcing), distribution center and warehouse system analysis, transportation systems design and analysis as well as design, control, planning, and evaluation of service enterprises, service quality management, service performance measurement, service supply chain management, design and reengineering of service processes, Human Resource Management in service organizations, and quantitative tools for managing service. Research output must lead to publication in international conference proceedings, or national/international refereed journal.

Course Description: Students will conduct research studies in the area of logistics and supply chain systems engineering or services science and engineering under the supervision of their thesis advisor. Research areas include production logistics analysis (production planning, inventory control, maintenance, reliability, scheduling specifically for and limited to logistics and supply chain systems), procurement logistics analysis (e-procurement, outsourcing, multiple sourcing)The first course in the independent study course series. Students conduct research studies in the area of logistics and supply chain systems engineering or services science and engineering under the supervision of their project advisors. Progress of the research studies must be reported at the end of semester. 

Course Description: Students will conduct research studies in the area of logistics and supply chain systems engineering or services science and engineering under the supervision of their thesis advisor. Research areas include production logistics analysis (production planning, inventory control, maintenance, reliability, scheduling specifically for and limited to logistics and supply chain systems), procurement logistics analysis (e-procurement, outsourcing, multiple sourcing)The first course in the independent study course series. Students conduct research studies in the area of logistics and supply chain systems engineering or services science and engineering under the supervision of their project advisors. Progress of the research studies must be reported at the end of semester. 

Course Description: Students will conduct research studies in the area of logistics and supply chain systems engineering or services science and engineering under the supervision of their project advisors. Progress of the research studies must be reported at the end of semester. Research output should lead to publication in international conference proceedings, or national/international refereed journal.