About the Upcoming Lecture Optimization is a foundational discipline across engineering, computer science, data science, management sciences, and policymaking. It helps organizations and public systems make the best possible decisions under defined constraints. With industries worldwide becoming increasingly data-driven, optimization has become a core analytical tool for improving efficiency, reducing costs, and balancing multiple objectives. This lecture aims to make these ideas accessible and practically understandable through examples that reflect real operational challenges. Dr. Singh will begin the session by introducing the essence of optimization-how decision variables, objective functions, and constraints come together to form a mathematical model of a practical problem. He will explain how optimization supports a wide range of applications such as supply chain management, AI-assisted decision-making, logistics, scheduling, healthcare operations, and large-scale public planning

The Department of ACSE, VFSTR, is delighted to announce that it is organizing a guest lecture titled "Understanding Optimization through Case Studies", to be delivered by Dr. Sujeet Kumar Singh, a distinguished academician and researcher known for his extensive contributions to operations research, mathematical optimization, multi-objective modelling, and advanced decision-making techniques. This upcoming session is planned as an engaging workshop-style lecture, offering students, researchers, and faculty members an opportunity to explore optimization through thoughtfully selected case studies representing real-world applications. About the Upcoming Lecture Optimization is a foundational discipline across engineering, computer science, data science, management sciences, and policymaking. It helps organizations and public systems make the best possible decisions under defined constraints. With industries worldwide becoming increasingly data-driven, optimization has become a core analytical tool for improving efficiency, reducing costs, and balancing multiple objectives. This lecture aims to make these ideas accessible and practically understandable through examples that reflect real operational challenges. Dr. Singh will begin the session by introducing the essence of optimization-how decision variables, objective functions, and constraints come together to form a mathematical model of a practical problem. He will explain how optimization supports a wide range of applications such as supply chain management, AI-assisted decision-making, logistics, scheduling, healthcare operations, and large-scale public planning. Topics to Be Covered During the Lecture 1. Transportation Optimization One of the major case studies in the lecture will focus on the Transportation Problem, a classical yet highly relevant optimization model used extensively in logistics and supply chain systems. Dr. Singh will discuss how organizations determine the most cost-effective ways to distribute goods from several source points to multiple destination points. He will use relatable examples from retail distribution networks, e-commerce fulfillment centres, manufacturing systems, and food supply chains. Participants will gain insights into how transportation models: @ minimize total operational costs, @ maintain supply-demand equilibrium, @ simplify routing decisions at scale, and @ improve delivery performance and customer service. 2. Facility Location Optimization The session will also cover the strategic problem of Facility Location Optimization, which helps organizations determine optimal locations for warehouses, hospitals, service centres, and production facilities. Dr. Singh will explain how mathematical modelling assists organizations in evaluating factors such as transportation distance, operational cost, demand patterns, response times, and service accessibility. By exploring case studies in data centre placement, public health infrastructure planning, and warehouse location decisions, attendees will learn how facility location models support long-term planning and decision-making. These models help businesses and governments minimize total operational effort while maximizing service efficiency, making facility planning a critical area of modern optimization. 3. Scheduling Optimization Another important topic that will be explored during the lecture is Scheduling Problems, which involve efficiently allocating resources and sequencing tasks. Dr. Singh will discuss real-life examples from: $ industrial job scheduling, $ academic timetable preparation, $ hospital operating room allocation, $ workflow management in IT systems, and $ task scheduling in cloud computing. Through these examples, he will demonstrate how systematic scheduling reduces waiting times, improves productivity, balances workloads, and ensures optimal resource utilization. The session will highlight how even small enhancements in scheduling strategies can significantly improve performance when dealing with large operational systems. 4. Introduction to Goal Programming (GP) A major highlight of the guest lecture will be an extensive introduction to Goal Programming (GP), one of the most widely used techniques for solving multi-objective optimization problems. Unlike single-objective models that focus on only one goal (such as minimizing cost), goal programming helps decision-makers satisfy multiple conflicting objectives by setting priorities and minimizing deviations from desired outcomes. Dr. Singh will explain how goal programming models are constructed, how priorities are assigned, and how decision-makers interpret solutions in real-world contexts. This section will be especially valuable for students and researchers interested in multi-criteria decision-making, sustainability modelling, and public systems optimization. 5. Application to Municipal Solid Waste (MSW) Management To demonstrate the real-life relevance of goal programming, Dr. Singh will present a practical example based on Municipal Solid Waste (MSW) Management, an essential component of sustainable urban development. He will explain how municipal authorities need to manage numerous conflicting objectives, such as: - minimizing waste collection and transportation costs, - meeting environmental standards, - ensuring timely waste pickup, - reducing health hazards, and - operating within strict budgetary limits. The case study will show how optimization helps city planners design efficient waste collection routes, plan facility locations, and allocate resources effectively. This example highlights how mathematical models directly contribute to achieving societal, environmental, and economic goals. Why Students Should Attend The upcoming lecture is designed to give students a solid conceptual foundation as well as practical insights into the real-world applications of optimization. Attending this lecture will help participants: @ understand the relevance of optimization in modern industries, @ gain exposure to classical and advanced optimization problems, @ explore research opportunities in multi-objective modelling, @ connect mathematical concepts with real-world case studies, and @ understand how optimization integrates with AI, data science, and decision analytics. Who Should Attend? The session will be particularly useful for: & undergraduate and postgraduate engineering students, & data science and AI learners, & operations research enthusiasts, & faculty members exploring interdisciplinary teaching, & researchers working on decision-making models, and & anyone interested in analytical problem-solving. The Department of ACSE at VFSTR is proud to host this academic event, which promises to offer tremendous learning value to students and faculty alike. With Dr. Sujeet Kumar Singh’s expertise and experience, the lecture is expected to provide deep insights into optimization and inspire participants to explore advanced topics in operational modelling, analytics, and applied mathematics. All students and faculty members are invited to join this enriching session and make the most of this valuable opportunity.