Scroll to top

Optimising Complex Army Logistics: Gurobi Solver Triumph


In the ever-evolving landscape of optimisation and logistics, Decision Lab’s cohort management project stands out thanks to the scale of it challenges and the success of its results.

The project, set within the demanding context of army training logistics, required a solution that could handle a massive scale of resources and consider a complex network of constraints and objectives. In finding an efficient solution, fulfilling the task helped revolutionise the way resources were managed, allocated, and optimised.

This article provides details of the project, the formidable optimisation challenges it presented, and demonstrates how the Gurobi solver, with its state-of-the-art capabilities, emerged as the ideal solution, surpassing other tools in efficiency, accuracy, and reliability.

Project Brief

The project was conceptualised with a vision to enhance the efficiency and effectiveness of army training programs through optimised resource management. The project aimed to create a dynamic system capable of intelligently allocating resources such as equipment, personnel, and training facilities. The challenge was not only to meet the diverse and fluctuating demands of various training modules but also to ensure that the allocation was cost-effective, met logistical constraints, and adhered to the stringent requirements of military training protocols. The success of the project hinged on its ability to achieve a delicate balance between maximising resource utilisation and minimising operational costs, all while navigating through a myriad of logistical and practical constraints.

Dashboard of logistics optimisation tool
Indicative user interface, providing clickable map and statistics dashboard.

Optimisation Task in Detail

At the core of the project was a complex optimisation task that required a sophisticated and multifaceted approach. The objective was to develop an optimisation model that could effectively manage the allocation of resources, ensuring that each training module received the necessary resources while maintaining overall operational efficiency.

The model needed to account for various constraints, including the limited availability of resources, the diverse needs of different training modules, and logistical considerations such as transportation and location constraints. This optimisation task was critical to the project’s success, as it directly impacted the efficiency and effectiveness of the training programs.

The challenge lay in creating a solution that was not only feasible and compliant with all constraints but also optimised to deliver the best possible outcomes in terms of resource utilisation and cost efficiency.

Difficulty of Solving the Optimisation Problem

The optimisation problem presented by the project was a formidable challenge. It involved a vast number of variables, each representing different aspects of the training resources and their potential allocations. The complexity was further compounded by the intricate and often conflicting constraints that had to be considered. Traditional optimisation solvers struggled to cope with this level of complexity, often resulting in prolonged computation times and sub-optimal solutions. The need for a more robust and capable optimisation tool was evident – one that could handle the computational demands and complexity of the task while delivering accurate and efficient solutions.

In this challenging scenario, the Gurobi solver emerged as the standout solution. Renowned for its advanced mathematical algorithms, Gurobi excels in efficiently navigating complex optimisation problems. Its ability to leverage modern hardware through parallel processing significantly accelerates computation times, a crucial factor in handling large-scale, complex tasks.

The Gurobi solver’s robustness in dealing with a wide range of constraints and its precision in finding optimal solutions set it apart from other solvers. These features made Gurobi not just a suitable choice for the project but a superior one, capable of overcoming the obstacles that other solvers could not surmount.

Experiment Results

To demonstrate Gurobi’s effectiveness, a series of experiments were conducted, comparing its performance against other optimisation tools in solving the project’s challenges. The results were clear and compelling.

In scenarios where other solvers either failed to find solutions or took an impractically long time, Gurobi consistently delivered high-quality solutions in significantly shorter time-frames. These experiments, encompassing various scenarios with different constraints and sets of variables, demonstrated Gurobi’s superior efficiency and effectiveness.

The findings, presented through detailed graphs and tables, illustrated Gurobi’s unmatched ability to solve complex optimisation tasks swiftly and accurately.

Small instance2.93s10.48s
Medium instance22.57s125.63s
Large instance57.41s997.21s
Decision Lab benchmarking results. Gurobi solver versus COIN-OR Branch and Cut solver (CBC).


The remarkable success of the Gurobi solver in the cohort management project not only highlights its superiority in tackling complex optimisation challenges but also underscores the transformative potential of advanced optimisation tools in resource management and logistics.

Gurobi’s performance in this project demonstrates how effective optimisation can lead to substantial improvements in efficiency, cost savings, and operational excellence. As we encounter increasingly complex optimisation problems in various fields, tools like Gurobi will become indispensable in quickly finding solutions that are not just feasible but also optimal, paving the way for innovation and progress in optimisation technology.

Learn more about decision intelligence and explore how we can help you optimise your operations. Contact us today!

Author avatar
Decision Lab
We use cookies to give you the best experience.