#operationsresearch

[damilola-doodles]

🎈Project Title: Integrated Renewable Energy Production Forecasting and Grid Stability Optimization.🍬🫖

ai-ml-ds-energy-optimization-forecasting-stability-023 Filename: renewable_grid_optimization.py Timestamp: Mon Jun 02 2025 19:46:55 GMT+0000 (Coordinated Universal Time) Problem Domain:Energy Systems, Power Grid Management, Renewable Energy Integration, Time Series Forecasting, Mathematical Optimization, Operations Research, Smart Grids. Project Description:This project tackles the dual…

[dammyanimation]

🎈Project Title: Integrated Renewable Energy Production Forecasting and Grid Stability Optimization.🍬🫖

ai-ml-ds-energy-optimization-forecasting-stability-023 Filename: renewable_grid_optimization.py Timestamp: Mon Jun 02 2025 19:46:55 GMT+0000 (Coordinated Universal Time) Problem Domain:Energy Systems, Power Grid Management, Renewable Energy Integration, Time Series Forecasting, Mathematical Optimization, Operations Research, Smart Grids. Project Description:This project tackles the dual…

[damilola-ai-automation]

🎈Project Title: Integrated Renewable Energy Production Forecasting and Grid Stability Optimization.🍬🫖

ai-ml-ds-energy-optimization-forecasting-stability-023 Filename: renewable_grid_optimization.py Timestamp: Mon Jun 02 2025 19:46:55 GMT+0000 (Coordinated Universal Time) Problem Domain:Energy Systems, Power Grid Management, Renewable Energy Integration, Time Series Forecasting, Mathematical Optimization, Operations Research, Smart Grids. Project Description:This project tackles the dual…

[damilola-warrior-mindset]

🎈Project Title: Integrated Renewable Energy Production Forecasting and Grid Stability Optimization.🍬🫖

ai-ml-ds-energy-optimization-forecasting-stability-023 Filename: renewable_grid_optimization.py Timestamp: Mon Jun 02 2025 19:46:55 GMT+0000 (Coordinated Universal Time) Problem Domain:Energy Systems, Power Grid Management, Renewable Energy Integration, Time Series Forecasting, Mathematical Optimization, Operations Research, Smart Grids. Project Description:This project tackles the dual…

[damilola-moyo]

🎈Project Title: Integrated Renewable Energy Production Forecasting and Grid Stability Optimization.🍬🫖

ai-ml-ds-energy-optimization-forecasting-stability-023 Filename: renewable_grid_optimization.py Timestamp: Mon Jun 02 2025 19:46:55 GMT+0000 (Coordinated Universal Time) Problem Domain:Energy Systems, Power Grid Management, Renewable Energy Integration, Time Series Forecasting, Mathematical Optimization, Operations Research, Smart Grids. Project Description:This project tackles the dual…

[mysteriouslymurkytrickster]

Richard C. Larson, often referred to as “Doctor Queue” for his pioneering work in queueing theory, has spent more than five decades transforming how we think about problem-solving in both academia and society. A professor at MIT for most of his life, Larson’s influence spans across operations research, public systems, and technology-enhanced learning. His career exemplifies how the union of intellectual rigor, field engagement, and deep humanism can generate lasting impact.

Larson began his journey at MIT, first as a student and later as a professor, immersing himself in the evolving discipline of operations research (OR). He was drawn to the science of improving decision-making through mathematics and systems thinking. But for Larson, OR was never just about elegant models—it was about solving real, messy problems that affect everyday lives. He frequently described it as “research on operations,” underscoring his preference for ground-level engagement over abstract theorizing.

One of Larson’s most celebrated achievements was the optimization of New York City’s 911 emergency response system. Through sophisticated applications of queueing theory and data-driven analysis, his work significantly cut response times and enhanced emergency resource allocation. This wasn’t just an academic exercise—it had tangible, life-saving results. For Larson, the impact of such improvements reaffirmed his core belief: theory must be fused with practice to serve the public good.

Larson was also a deeply committed educator and mentor. He rejected the traditional “theorem-proof” pedagogy in favor of immersive, real-world learning. In his classes, students tackled ambiguous, complex problems that required both analytical precision and human judgment. Through hands-on fieldwork and consulting opportunities—including partnerships with agencies like the U.S. Postal Service and the City of New York—Larson instilled in his students a profound respect for the operational environments they were trying to improve. Many of those he mentored have gone on to become influential figures in their own right, echoing his interdisciplinary and impact-driven ethos.

Education, however, was not confined to MIT’s campus. Larson’s vision for technology-enabled learning took shape during his directorship at MIT’s Center for Advanced Educational Services (CAES) from 1995 to 2003. He recognized early on how digital tools could democratize access to high-quality education. Under his leadership, CAES laid the groundwork for MIT’s future innovations in online and blended learning.

In 2002, Larson founded the Learning International Networks Consortium (LINC), a global initiative designed to bring together educators, policymakers, and technologists committed to expanding educational access through digital means. LINC has since impacted learners and institutions across more than 25 countries, creating a platform for shared learning and global collaboration.

Perhaps his most enduring contribution to educational technology is MIT BLOSSOMS (Blended Learning Open Source Science Or Math Studies). Inspired by a visit to a rural school in China, Larson envisioned video-based, interactive STEM lessons that could support—not replace—teachers in under-resourced environments. Today, BLOSSOMS offers free, globally-sourced modules that help students engage with complex concepts through active learning. It stands as a model of how blended learning and open educational resources can bring equity and excellence to classrooms around the world.

Larson’s scholarly output is vast, but always grounded in accessibility and practicality. His most recent book, MODEL THINKING For Everyday Life, encourages general audiences to apply the same modeling techniques used in operations research to daily decision-making. He champions what he calls “model thinking”—not just using models, but developing a mindset of structured inquiry and analysis. In an era where people increasingly rely on algorithms and automation, Larson’s message is clear: human intelligence, critical thinking, and experiential learning are more vital than ever.

In addition to shaping academia and public systems, Larson has left a mark through leadership in professional societies like INFORMS (Institute for Operations Research and the Management Sciences), where he served as president. His collaborative spirit and strategic insight helped grow operations research into a dynamic, interdisciplinary field with real-world relevance.

On a personal note, Larson’s life is also one of balance and values. With his wife, Mary Elizabeth Murray (“Liz”), he has navigated the demands of academia and public engagement while prioritizing family and community. Colleagues and students alike speak of his generosity, accessibility, and tireless commitment to making the world a better place.

Conclusion Richard C. Larson’s life and work illustrate the transformative power of interdisciplinary thinking, public service, and educational innovation. Whether optimizing emergency systems, mentoring the next generation, or revolutionizing global STEM education, Larson has always kept one goal in sight: improving the systems that shape people’s lives. His legacy is not only written in papers and policies but also in the lives he has touched and the communities he has strengthened. In a rapidly changing world, Larson stands as a powerful reminder that the fusion of science, empathy, and vision can truly change the world.

Read more: Richard C. Larson: A Lifetime of Innovation in Operations Research and Education

[strategyawards]

#sciencefather |🔍 Differential Game Model of Fresh Supply Chain 🥬📦#SupplyChain #DifferentialGame

🏆 International Research Awards on Strategic Management & Business Strategy 🌍📈

In this video, we dive into a cutting-edge differential game model designed for fresh supply chains 🍓🥦. Discover how preservation strategies, behavioral decisions of supply chain members, and government subsidies interact to optimize supply chain performance. 📌 Key Topics Covered: ✅ Dynamic modeling of fresh product supply chains ✅ Role of preservation investment 🧊 ✅ Strategic decision-making of suppliers & retailers 🤝 ✅ Impact of government support & subsidies 🏅💵 ✅ Sustainable and efficient operations 🌱🚛 This research-based model offers valuable insights for academics, policymakers, and supply chain managers aiming to enhance fresh product quality, reduce waste, and promote collaborative practices in the agri-food sector.

visit : https://business-strategy-conferences.scifat.com/ Nomination link : https://business-strategy-conferences.scifat.com/award-nomination/?ecategory=Awards&rcategory=Awardee Registration link: https://business-strategy-conferences.scifat.com

📚 Based on advanced game theory and control models. 👍 Like, 💬 Comment, and 🔔 Subscribe for more research insights! 🎯 Celebrating excellence in: 📚 Academic Research 💼 Business Innovation 📊 Strategic Decision-Making 🌐 Global Management Practices 🏅 Honoring top minds in: 🔍 Strategic Planning 🚀 Competitive Advantage 🧠 Organizational Behavior 📘 Corporate Governance 🤝 Leadership & Collaboration Join the global conversation and witness how research shapes the future of business strategy and management science!

[shristisahu]

#Revolutionizing Supply Chain Efficiency through Network Optimization

Originally Published on: QuantzigSupply Chain Network Optimization Boosts Efficiency, Cuts Inventory by 65%

##Industry Overview In the dynamic realm of supply chain dynamics, a leading U.S. food manufacturing company faced intricate challenges due to the complexity of its supply network. To address this complexity and enhance overall performance, the company partnered with Quantzig, aiming to redesign its supply chain for increased efficiency in response to surging global demand and online sales.

Book a demo to explore meaningful insights derived from data through our analytical tools and platform capabilities. Schedule a demo today!

##The Business Challenge With supply chain operations impacting procurement costs and service efficiency, optimizing product flow became imperative. Unfortunately, many businesses neglect aligning their network optimization programs with long-term objectives. In response, Quantzig focuses on developing dynamic supply chain network optimization capabilities that align with both short-term efficiency gains and long-term strategic goals.

##Solutions Offered and Value Delivered Quantzig's analytics experts collaborated with the client, conducting a thorough evaluation, recommending operational enhancements, piloting changes, and finally implementing them. Leveraging internal supply chain data, the team uncovered several cost-saving opportunities.

Our supply chain network optimization solutions enabled the client to:

Enhance value creation: Implementing systematic order management systems. Achieve performance improvements: Streamlining internal clearance processes. Reduce inventory costs: Achieving a remarkable 65% reduction. Experience the advantages firsthand by testing a customized complimentary pilot designed to address your specific requirements. Pilot studies are non-committal in nature.

##Impacts of Supply Chain Network Optimization

###Enhanced Operational Efficiency Implementation of advanced analytics and optimization techniques streamlined warehouse expenses and supply chain networks, improving product availability and delivery speed. This led to optimized operational details, reduced excess capacity, mitigated shortages, and consolidated footprints, resulting in improved bottom-line numbers and heightened market competitiveness.

###Improved Agility and Responsiveness Incorporating optimization-derived designs and employing deep reinforcement learning allowed businesses to adapt to rapid demand growth and unforeseen disruptions. Continuous improvements and incremental changes enhanced the supply chain's resilience, ensuring uninterrupted service and meeting next-day delivery cutoffs, thus capitalizing on opportunities and maintaining customer satisfaction.

###Strategic Decision Making Multi-objective network optimization aligned organizational objectives with supply chain configurations, facilitating strategic growth initiatives and future expansion plans. Utilizing physics-inspired graph neural networks ensured unconstrained capacity networks supporting future growth strategies, fostering sustainable growth and a competitive advantage.

###Technological Advancement and Innovation Leveraging operations research-based tools and emerging technologies like combinatorial optimization with graph neural networks fueled innovation within the supply chain domain. This approach tackled complexities with novel strategies, fostering a culture of continuous improvement and keeping organizations at the forefront of supply chain management practices.

##Optimization Techniques and Technology

###Advanced Analytics for Data-Driven Insights Leverage advanced analytics to harness vast amounts of data within supply chain networks. Techniques such as network modeling and deep reinforcement learning analyze operational details, identify patterns, and inform decisions. Thought leadership in advanced analytics enables organizations to stay ahead, leveraging data as a strategic asset.

###Multi-Objective Network Optimization Embrace multi-objective network optimization approaches to balance conflicting goals within the supply chain. By optimizing across various dimensions like product availability, delivery speed, and cost efficiency, businesses achieve synergies and trade-offs aligning with strategic objectives.

###Integration of Cutting-Edge Technologies Integrate technologies like Combinatorial Optimization with Physics-Inspired Graph Neural Networks to tackle complex supply chain networks. By harnessing machine learning and graph neural networks, businesses address traditional supply chain problems, optimizing designs for maximum effectiveness and staying agile in evolving market dynamics.

###Continuous Improvement through Operations Research-Based Tools Embrace operations research-based tools for continuous improvement within the supply chain. This systematic approach identifies opportunities, evaluates scenarios, and makes data-driven decisions, enhancing supply chain resilience and improving overall operational efficiency.

###Strategic Alignment with Organizational Objectives Ensure optimization techniques and technology align with broader organizational objectives. Integrating optimization-driven supply chain network designs with the organizational structure fosters a cohesive framework for decision-making, resource allocation, and drives sustainable growth.

##How Can You Achieve Supply Chain Network Optimization?

Achieving supply chain network optimization requires a comprehensive approach integrating various strategies and technologies.

Utilize Advanced Analytics and Technologies: Leverage advanced analytics and technologies like deep reinforcement learning and operations research-based tools for thorough analysis.

Streamline Operational Processes: Focus on streamlining processes to improve delivery speed and product availability. Optimize inbound and outbound delivery options, utilize distributed storage networks, and explore different transport modes.

Align Organizational Objectives: Ensure alignment between organizational objectives and supply chain configurations. Develop a clear future growth strategy and organizational model supporting value-adding stages.

Continuous Improvement and Adaptation: Embrace a culture of continuous improvement to address evolving challenges. Implement incremental network changes based on feedback, market trends, and technological advancements.

Monitor Performance Metrics: Establish key performance metrics and regularly monitor bottom-line numbers. Analyze reports to track progress, identify areas for improvement, and make data-driven decisions.

Quantzig is a leading provider of advanced analytics and consulting services, known for its expertise in supply chain optimization. Our capabilities are characterized by a data-driven approach, advanced analytics, and a focus on delivering tangible business outcomes such as cost savings, improved service levels, and enhanced operational resilience.

Adopting a structured approach to supply chain network optimization can help businesses tackle complexities and achieve substantial reductions in inventory costs. Get started with your complimentary trial today and explore our range of customized, consumption-driven analytical solutions across different maturity levels.

Contact us.

[salvatoretirabassi]

Who’s on a quest to develop advanced data science capabilities? One of my analytics team’s strategic expansion brought together diverse talents in statistics, applied math, and engineering.

[damilola-doodles]

📌Project Title: Massive-Scale Public Transport Route Optimization using Network Analysis and Genetic Algorithms.🔴

ai-ml-ds-operations-research-transport-optimization-014 Filename: public_transport_route_optimization_ga.py Timestamp: Mon Jun 02 2025 19:31:21 GMT+0000 (Coordinated Universal Time) Problem Domain:Urban Planning, Transportation Engineering, Operations Research, Network Science, Optimization, Evolutionary Computation. Project Description:This project tackles the complex problem of optimizing…

[dammyanimation]

📌Project Title: Massive-Scale Public Transport Route Optimization using Network Analysis and Genetic Algorithms.🔴

ai-ml-ds-operations-research-transport-optimization-014 Filename: public_transport_route_optimization_ga.py Timestamp: Mon Jun 02 2025 19:31:21 GMT+0000 (Coordinated Universal Time) Problem Domain:Urban Planning, Transportation Engineering, Operations Research, Network Science, Optimization, Evolutionary Computation. Project Description:This project tackles the complex problem of optimizing…

[damilola-ai-automation]

📌Project Title: Massive-Scale Public Transport Route Optimization using Network Analysis and Genetic Algorithms.🔴

ai-ml-ds-operations-research-transport-optimization-014 Filename: public_transport_route_optimization_ga.py Timestamp: Mon Jun 02 2025 19:31:21 GMT+0000 (Coordinated Universal Time) Problem Domain:Urban Planning, Transportation Engineering, Operations Research, Network Science, Optimization, Evolutionary Computation. Project Description:This project tackles the complex problem of optimizing…

[damilola-warrior-mindset]

📌Project Title: Massive-Scale Public Transport Route Optimization using Network Analysis and Genetic Algorithms.🔴

ai-ml-ds-operations-research-transport-optimization-014 Filename: public_transport_route_optimization_ga.py Timestamp: Mon Jun 02 2025 19:31:21 GMT+0000 (Coordinated Universal Time) Problem Domain:Urban Planning, Transportation Engineering, Operations Research, Network Science, Optimization, Evolutionary Computation. Project Description:This project tackles the complex problem of optimizing…

[damilola-moyo]

📌Project Title: Massive-Scale Public Transport Route Optimization using Network Analysis and Genetic Algorithms.🔴

ai-ml-ds-operations-research-transport-optimization-014 Filename: public_transport_route_optimization_ga.py Timestamp: Mon Jun 02 2025 19:31:21 GMT+0000 (Coordinated Universal Time) Problem Domain:Urban Planning, Transportation Engineering, Operations Research, Network Science, Optimization, Evolutionary Computation. Project Description:This project tackles the complex problem of optimizing…