Retail & Consumer Products
Decisiveness During Uncertainty
Make optimal decisions—from store locations and inventory control, to supply chains and strategic marketing.
Retail & Consumer Products
Decisiveness During Uncertainty
Make optimal decisions—from store locations and inventory control, to supply chains and strategic marketing.
Retail & Consumer Products
Decisiveness During Uncertainty
Make optimal decisions—from store locations and inventory control, to supply chains and strategic marketing.
Overview
Gurobi helps companies identify how to deliver the right products to the right customers at the right time in order to create the best possible purchasing experience. From planning all the way through agile execution in the marketplace, Gurobi enabled optimal decision-making, including: deciding which locations have the greatest potential to support new stores, optimizing store layout to maximize space, analyzing which products to carry and how to merchandize them, inventory control, and determining which marketing elements will have the biggest impact on customer behavior.
Overview
Gurobi helps companies identify how to deliver the right products to the right customers at the right time in order to create the best possible purchasing experience. From planning all the way through agile execution in the marketplace, Gurobi enabled optimal decision-making, including: deciding which locations have the greatest potential to support new stores, optimizing store layout to maximize space, analyzing which products to carry and how to merchandize them, inventory control, and determining which marketing elements will have the biggest impact on customer behavior.
Overview
Gurobi helps companies identify how to deliver the right products to the right customers at the right time in order to create the best possible purchasing experience. From planning all the way through agile execution in the marketplace, Gurobi enabled optimal decision-making, including: deciding which locations have the greatest potential to support new stores, optimizing store layout to maximize space, analyzing which products to carry and how to merchandize them, inventory control, and determining which marketing elements will have the biggest impact on customer behavior.
Explore real-world problems in your industry
Dive deep into sample models, built with our Python API.
Market Sharing
In this example, we’ll show you how to solve a goal programming problem that involves allocating the retailers to two divisions of a company in order to optimize the trade-offs of several market sharing goals. You’ll learn how to create a mixed integer linear programming model of the problem using the Gurobi Python API and how to find an optimal solution to the problem using the Gurobi Optimizer. This model is example 13 from the fifth edition of Model Building in Mathematical Programming by H. Paul Williams on pages 267-268 and 322-324. This modeling example is at the beginner level, where we assume that you know Python and that you have some knowledge about building mathematical optimization models. You may also want to check out the documentation of the Gurobi Python API.
Customer Assignment
Marketing Campaign Optimization
Supply Network Design
Explore real-world problems in your industry
Dive deep into sample models, built with our Python API.
Market Sharing
In this example, we’ll show you how to solve a goal programming problem that involves allocating the retailers to two divisions of a company in order to optimize the trade-offs of several market sharing goals. You’ll learn how to create a mixed integer linear programming model of the problem using the Gurobi Python API and how to find an optimal solution to the problem using the Gurobi Optimizer. This model is example 13 from the fifth edition of Model Building in Mathematical Programming by H. Paul Williams on pages 267-268 and 322-324. This modeling example is at the beginner level, where we assume that you know Python and that you have some knowledge about building mathematical optimization models. You may also want to check out the documentation of the Gurobi Python API.
Customer Assignment
Marketing Campaign Optimization
Supply Network Design
Explore real-world problems in your industry
Dive deep into sample models, built with our Python API.
Market Sharing
In this example, we’ll show you how to solve a goal programming problem that involves allocating the retailers to two divisions of a company in order to optimize the trade-offs of several market sharing goals. You’ll learn how to create a mixed integer linear programming model of the problem using the Gurobi Python API and how to find an optimal solution to the problem using the Gurobi Optimizer. This model is example 13 from the fifth edition of Model Building in Mathematical Programming by H. Paul Williams on pages 267-268 and 322-324. This modeling example is at the beginner level, where we assume that you know Python and that you have some knowledge about building mathematical optimization models. You may also want to check out the documentation of the Gurobi Python API.
Customer Assignment
Marketing Campaign Optimization
Supply Network Design
"Gurobi's advancements go beyond performance to enhance usability, appealing to both beginner and expert users."
Gurobi 13.0 Beta Tester
"We’ve been doing optimization for decades, and Gurobi is simply the fastest and most reliable solver we’ve tested. We use it on every project."
"It’s not just about getting the best answer; it’s about giving advisors and clients a plan they can understand and trust. What would take hours to do manually, we can do in minutes, with better outcomes."
"Gurobi's advancements go beyond performance to enhance usability, appealing to both beginner and expert users."
Gurobi 13.0 Beta Tester
"We’ve been doing optimization for decades, and Gurobi is simply the fastest and most reliable solver we’ve tested. We use it on every project."
"It’s not just about getting the best answer; it’s about giving advisors and clients a plan they can understand and trust. What would take hours to do manually, we can do in minutes, with better outcomes."
"Gurobi's advancements go beyond performance to enhance usability, appealing to both beginner and expert users."
Gurobi 13.0 Beta Tester
"We’ve been doing optimization for decades, and Gurobi is simply the fastest and most reliable solver we’ve tested. We use it on every project."
"It’s not just about getting the best answer; it’s about giving advisors and clients a plan they can understand and trust. What would take hours to do manually, we can do in minutes, with better outcomes."
The Solver that Does More
Gurobi delivers blazing speeds and advanced features—backed by brilliant innovators and expert support.
With Gurobi’s advanced algorithms, you can add complexity to your models to better represent real-world systems—and still solve them within the available time.
Frequently Asked Questions
What is prescriptive analytics?
Prescriptive analytics tools like mathematical optimization help you make decisions based on your real-world business goals (“objectives”) and limitations (“constraints.”) This can be especially useful when you’re facing a business problem with multiple, conflicting goals (such as cutting spending while increasing production) and multiple constraints (such as time, distance, product availability).
Learn more about prescriptive analytics in our article, “What is Prescriptive Analytics?”
What is the difference between predictive and prescriptive analytics?
What are some examples of prescriptive analytics in the real world?
How can prescriptive and predictive analytics work together?
What is the primary goal of prescriptive analytics?
What are the techniques used in prescriptive analytics?
What is prescriptive analytics also known as?
Frequently Asked Questions
What is prescriptive analytics?
Prescriptive analytics tools like mathematical optimization help you make decisions based on your real-world business goals (“objectives”) and limitations (“constraints.”) This can be especially useful when you’re facing a business problem with multiple, conflicting goals (such as cutting spending while increasing production) and multiple constraints (such as time, distance, product availability).
Learn more about prescriptive analytics in our article, “What is Prescriptive Analytics?”
What is the difference between predictive and prescriptive analytics?
What are some examples of prescriptive analytics in the real world?
How can prescriptive and predictive analytics work together?
What is the primary goal of prescriptive analytics?
What are the techniques used in prescriptive analytics?
What is prescriptive analytics also known as?
Additional Insights
Case Studies
Case Studies
Luca: Transforming Grocery Pricing with Real-Time Price Optimization
Luca enables grocery retailers to optimize prices across tens of thousands of products in seconds, with a single click.
Case Studies
Sixt Portugal: Driving Better Decisions and Optimized Revenue Management
Sixt Portugal uses real-time optimization to improve pricing and fleet rotation across 42 stations nationwide.
Case Studies
Blue Yonder: Retail Pricing Decisions
Blue Yonder delivers AI-powered retail price optimization that increases sales and profits for the world's leading retailers.
Additional Insights
Case Studies
Case Studies
Luca: Transforming Grocery Pricing with Real-Time Price Optimization
Luca enables grocery retailers to optimize prices across tens of thousands of products in seconds, with a single click.
Case Studies
Sixt Portugal: Driving Better Decisions and Optimized Revenue Management
Sixt Portugal uses real-time optimization to improve pricing and fleet rotation across 42 stations nationwide.
Additional Insights
Case Studies
Case Studies
Luca: Transforming Grocery Pricing with Real-Time Price Optimization
Luca enables grocery retailers to optimize prices across tens of thousands of products in seconds, with a single click.
Case Studies
Sixt Portugal: Driving Better Decisions and Optimized Revenue Management
Sixt Portugal uses real-time optimization to improve pricing and fleet rotation across 42 stations nationwide.
Case Studies
Blue Yonder: Retail Pricing Decisions
Blue Yonder delivers AI-powered retail price optimization that increases sales and profits for the world's leading retailers.
Start Solving with Gurobi
Try Gurobi on your own optimization models and see how it performs on real decision problems.
Start Solving with Gurobi
Try Gurobi on your own optimization models and see how it performs on real decision problems.
