For decades, supply chain leaders have relied on tools that depend on predefined assumptions to drive transformation and make changes to their network design. However, supply chains of today have great complexity and face much volatility. Due to this, network optimisation teams find that traditional network design tools fall short and cannot deliver the innovation they seek.
Built from linear programming, traditional network design tools often require rigid inputs and steers. This constrains leaders, forcing them to assume what they need to find out. Consequently, over time, these assumptions cause inefficiencies, which root themselves deep within the network. This can lead to significant loss of value across the supply chain.
Of course, challenging the ‘what we’ve always done’ of network design can feel impossible. Leaders find it difficult to tackle groupthink or explore alternative strategies. However, fear of the unknown ultimately limits innovation, resulting in missed opportunities for optimisation.
To move beyond fixed assumptions and uncover transformative value, we need a more dynamic approach to network design. Genetic algorithms, inspired by the principles of natural selection, offer exactly that. These algorithms enable expansive, unconstrained search for high performing network configurations.
Unlike traditional tools, network design technology powered by genetic algorithms can rapidly evaluate thousands of network designs. This allows businesses to explore the impacts of proposed innovation, maximise trade-offs between priority KPIs and gain better insights into the drivers of performance.
Turning network design into an engine for growth with genetic algorithms
In a world defined by volatility, managing uncertainty becomes increasingly more critical. Faced with geopolitical uncertainties and climate disruptions, leaders need the ability and resources to explore change in a risk-free environment.
Equally, as companies scale, seek to reduce costs, or look to manage the rise in demand from e-commerce, the complexity of their decisions inevitably grows. This can include adding or removing facilities across the network, consolidating facilities, or introducing ‘milk runs’. Or, perhaps, supply chain segmentation, modal shift, or just a desire to understand how best to reduce costs and increase speed to customers.
Having a robust network design doesn’t just promise resilience - it can also help businesses gain competitive advantage. With the right tools, leaders can uncover hidden optimisation opportunities and identify drivers of high performance. Such heuristics can then inform strategic decision making to significantly reduce costs, shorten lead times and lower emissions.
Network design is no longer a one-off exercise. It’s a continuous, strategic process and a key differentiator for future-ready supply chains.
Genetic algorithms for driving optimal transformation
Inspired by the process of natural selection, genetic algorithms iteratively evolve network structures to find optimal configurations. They do this by applying evolutionary principles such as crossover, mutation, and selection - continually refining network designs in pursuit of higher performance.
In each iteration, termed a ‘generation’, the algorithm generates a population of potential network configurations and evaluates each one against specific performance objectives set by the user, such as cost, resilience or sustainability. The algorithm then selects high-performing designs, combines and modifies their traits associated with high performance, and creates a new generation. With each cycle, the network designs become more and more optimal.
Each individual structure generated by the algorithm represents a unique configuration of the network. Rather than relying on fixed assumptions or linear models, genetic algorithms explore a vast range of possibilities, continuously learning and adapting to improve performance. This process uncovers optimised structures that traditional methods often cannot reach.
By simulating thousands of scenarios in parallel, the technology gives leaders intuitive insights into how their networks will perform across a range of configurable scenarios. This empowers leaders to break free from assumptions, challenge groupthink and make smarter decisions with confidence.
The groundbreaking network design technology that’s powered by genetic algorithms
The future of network design has arrived. Our revolutionary network design technology is a game-changer for leaders looking to optimise transformation of their complex supply chain and logistics networks.
Powered by genetic algorithms, simulation and AI, our network design technology enables unconstrained search to reveal the optimal network structure for any desired transformation.
Most importantly, our cutting-edge technology offers a risk-free, virtual environment to test innovation. The platform delivers insights to reveal the impact of strategic changes, helping leaders build business cases for proposed transformation.
We can also test uncertainties across various disruption scenarios, enabling faster decision making and proactivity.
This technology, coupled with our expertise and seamless integration, is saving our industry-leading clients hundreds of millions each year, while accelerating their network optimisations.
Transform your network with unconstrained search
In a world defined by constant change and growing complexity, leaders need to prioritise network design. By leveraging unconstrained search and genetic algorithms, there exists a huge opportunity for businesses to get ahead of their competitors and start drawing more value from their networks.
Ready to unlock the full potential of your supply chain network? Email us at info@hackandcraft.com today to see our groundbreaking network design technology for yourself.
