Product & Services
Inventory Modelling
Our inventory management model is designed to effectively handle both deterministic and probabilistic demand scenarios, making it a reliable solution for businesses looking to streamline their operations and optimize their inventory levels.
Assignment Model
The assignment model is a mathematical tool used to optimize the allocation of resources to tasks. The Hungarian algorithm is an efficient computational method used to solve this model. It works by finding the minimum cost assignment in a matrix of costs between resources and tasks. The Traveling Salesman algorithm is another optimization algorithm that is used to find the shortest possible route that visits all points in a given set. It is commonly used in logistics and transportation planning, where it helps to minimize travel time and distance while maximizing efficiency.
Integer Linear programming
Integer linear programming (ILP) is a powerful optimization technique that is particularly useful when the solution requires integer values. In many real-world scenarios, we cannot settle for fractional values because they do not make sense in the context of the problem. ILP helps us find the best integer solution to problems like determining the optimal number of workers for a production activity or the number of components to produce. By ensuring that the solution is an integer, we can achieve the most efficient outcome and avoid any potential errors or inaccuracies that might arise from using fractional values.
Transportation Model
These methods involve finding the optimal solution that minimizes the total transportation cost of transferring goods from a set of sources to their destination, based on the demand of the region. By using these techniques, businesses can efficiently allocate their resources and reduce overall transportation costs while ensuring that goods reach their intended destination.
Queuing Model
A multi-server queuing model is a system in which multiple servers work together to serve customers in a queue. This type of model is useful when there are high service demands and customers may experience long waiting times. By utilizing multiple servers, the system can better manage customer traffic and optimize service efficiency.
Mixed Integer Linear Programming
Mixed integer linear programming is a more flexible variant of integer linear programming that allows certain variables to take on fractional values in addition to integer values. This relaxation of the constraints can result in a more accurate representation of real-world problems, where not all solutions need to be strictly integer. By combining the power of linear programming with the added flexibility of mixed integer programming, this algorithm can produce efficient and effective solutions to a wide range of optimization problems.
Sensitivity analysis
Sensitivity analysis is a mathematical method used to determine how changes in input parameters affect the output of a mathematical model. It helps to identify the range of values within which the input parameters can change without significantly affecting the results of the model. This analysis is useful in decision-making processes where the decisions are dependent on the results of the model.
Simplex Algorithm
Simplex algorithm is a linear programming technique that helps us to find the optimal solution of a given linear model. Here we establish a linear relationship with our resources and consumables then we converge our results by maximizing our profit, rate of production, etc., or by minimizing the total cost, production time, etc.
Production Planning
Production planning is a crucial process that involves deciding how a product is to be manufactured before the actual production process begins. It takes into account the results obtained from various mathematical models such as linear programming models, inventory models, and assignment models. The primary objective of production planning is to meet the demand from different regions while optimizing production rates and resource consumption. This becomes particularly important when the product is to be manufactured in multiple phases, as the focus is on reducing the idle time per phase. Effective production planning helps in ensuring that the production process is efficient, cost-effective, and meets the required quality standards.”
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Operations Analytics
Operations analytics is a pivotal area of business intelligence that focuses on improving operational efficiency and effectiveness by analyzing data to uncover insights, optimize processes, and drive informed decision-making. It involves using advanced analytical tools and techniques to enhance various aspects of operations such as resource utilization, supply chain management, performance monitoring, and risk assessment. By harnessing the power of data-driven insights, organizations can streamline their operations, reduce costs, mitigate risks, and ultimately achieve greater levels of productivity and competitiveness.
Operations AI
Operations AI leverages artificial intelligence and machine learning technologies to enhance operational processes, automate tasks, and drive efficiencies in various business functions. By integrating AI algorithms into operations management, organizations can optimize resource allocation, predict maintenance needs, improve demand forecasting, streamline production workflows, and enhance customer service experiences. Operations AI enables real-time decision-making based on data-driven insights, resulting in increased productivity, reduced costs, improved quality control, and overall operational excellence. Embracing AI in operations empowers businesses to stay competitive in today’s rapidly evolving digital landscape.
Clients We’ve Worked With
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When connected with us, you aren’t growing your business alone. We have your back and put in our best to contribute to the growth of your entire team and organization. If you are looking for the right analytics tool that’ll help you to manage your operations, we are right here!