Copsolver: Create a Future of Industrial Decision Efficiency

The world of decision-making is full of choices and constraints, a complex dance that affects everything from industrial operations to daily life. Imagine that the best choice must be chosen from the myriad possibilities, each need to be consistent with certain rules and contribute to a specific goal. This is the area of decision-making and optimization challenges found in the industrial environment and in our daily decision-making. Successfully addressing these issues promises to achieve significant benefits: Increase efficiency, reduce costs, increase productivity, extend equipment life, make smarter choices, and improve customer satisfaction. Despite the various ways to deal with these multifaceted challenges, it is rare to find software solutions. Often, the available software is proprietary and designed for very specific organizational issues, with the creators having access to it. What is even more worrying is that many software solutions developed in research environments are still not disclosed and eventually disappear.
In this case, Copsolver is a groundbreaking innovation. Developed by Professor Tatiana Balbi Fraga of Pernambuco Federal University and published in Journal Software Explists, this free access software revolutionized how complex decision-making tasks are handled in an industrial environment. Copsolver’s growth continues to use two new libraries for multi-criteria ABC classification and demand pattern recognition. Professor Fraga is passionate about its expansion, saying: “I am happy to detail these in the upcoming article and are developing more libraries for demand forecasting and complete production plans.” Plans to adapt existing software to Further enhance the functionality of Copsolver. Copsolver’s first library aims to optimize the processing time of multiple products co-made, each with different productivity. This is more than just a tool; it is a significant leap in managing complex industrial decisions.
At the heart of Copsolver’s first library is its approach to optimizing these multi-product manufacturing processes. “So, I have developed Copsolver to provide everyone with scientific tools that can help improve the decision-making process and improve the efficiency of various organizational processes,” explains Professor Fraga. This is especially important in an industry that produces multiple products simultaneously, every It takes different time to produce products. The challenge is to find out the optimal production time for these mixed product batches, taking into account various restrictions and requirements. By effectively addressing this challenge, Copsolver’s first library has brought huge benefits to the industry, thereby improving stock control and improving productivity.
Copsolver’s first library is more in-depth, with low operating costs and high efficiency. It uses the method taught by Professor Fraga to ensure fast and accurate solutions for complex optimization tasks. The software architecture is powerful and adaptable, written in a programming language called C++ and structured to handle a series of optimization tasks. Each problem is defined and resolved in its specific section to ensure that the problem is resolved.
Copsolver has a wide influence. In the industrial sector, it improves the efficiency of planning and production of products, which is an important part of production management. Professor Fraga’s highlight: “Determining the optimal production time for mixed product batches is critical to certain industries as it is directly related to stock management and meeting customer needs”. This efficiency helps better control stocks and meet customer needs, thereby increasing costs and increasing customer satisfaction. The freely accessible nature of the software ensures that it can be widely used in various industries.
With an ambitious vision, Professor Fraga aims to compete for the terminology of Copsolver for validity and simplicity. “Our goal is to effectively solve any decision-making or optimization problems,” she notes, highlighting the software’s potential to change decisions through collaborative efforts. Looking to the future, Professor Fraga led a team envisioning a bright future for Copsolver. Their goal is to expand their capabilities to address broader challenges and approaches, making them an important tool for small businesses. By training these companies to use Copsolver, the team hopes to enhance their competitive potential and drive innovation and advancement in their business landscape.
In short, Copsolver represents an important step in the field of decision-making and optimization of software. Its development not only addresses specific industrial challenges, but also lays the foundation for widespread use in various sectors. As the industry continues to grow and seek optimized solutions, Copsolver represents the power of innovative software development in improving efficiency and progress.
Journal Reference
Tatiana Balbi Fraga, “Copsolver: Open Source Software for Solving Combination Optimization and Other Decision Maximization Problems – Library for Solving Multi-Product P-Batch Processing Time Maximization Problems”, Software Impact, 2023. DOI: https://doi.org/ 10.1016/j.simpa.2023.100592
About the Author
Dr. Tatiana Balbi Fraga The Rio de Janeiro Polytechnic Institute is the Rio de Janeiro State University, and is an MS and PhD in Computational Modeling. Currently, she is an associate professor of production engineering at Penangbuco Federal University and the founder of the “System Analysis, Modeling and Optimization Group” (GAMOS). Dr. Fraga has developed technology, research and extension work, especially mathematical modeling and optimization of standard problems extracted from scientific literature, as well as practical problems, especially industrial problems and areas of combination optimization. The teacher received ten from her master’s degree, engaged in problem-oriented programming and recently developed and released the open source software Copsolver, a structure that features a problem-oriented programming structure.