Recently, one of our consortium partners in the project, CIGIP-UPV, presented their contributions in the Wood2Wood project at ICE/IEEE ITMC held in Valencia, Spain. Javier Cuartas, Raul Poler and Josรฉ Antonio Comesaรฑa Benavides presented two conference papers at ICE 2025 on “๐ถ๐๐๐๐๐๐๐๐๐๐๐ ๐จ๐๐๐๐๐๐๐๐๐ ๐๐ ๐พ๐๐๐
๐บ๐๐๐๐๐ ๐ช๐๐๐๐ ๐ด๐๐๐๐๐๐๐๐๐”.
โก๏ธ๐๐ฉ๐ญ๐ข๐ฆ๐ข๐ณ๐๐ญ๐ข๐จ๐ง ๐๐ฉ๐ฉ๐ซ๐จ๐๐๐ก๐๐ฌ ๐ข๐ง ๐๐จ๐จ๐ ๐๐ฎ๐ฉ๐ฉ๐ฅ๐ฒ ๐๐ก๐๐ข๐ง ๐๐๐ง๐๐ ๐๐ฆ๐๐ง๐ญ: A Multi-Problem Perspective Based on Sustainability and Circular Economy.
โก๏ธ๐๐ฉ๐ญ๐ข๐ฆ๐ข๐ณ๐๐ญ๐ข๐จ๐ง ๐๐ฉ๐ฉ๐ซ๐จ๐๐๐ก๐๐ฌ ๐ข๐ง ๐๐จ๐จ๐ ๐๐ฎ๐ฉ๐ฉ๐ฅ๐ฒ ๐๐ก๐๐ข๐ง ๐๐๐ง๐๐ ๐๐ฆ๐๐ง๐ญ: Facility Location Problem, A Metaheuristic-Enhanced Approach
In the first paper, authors Javier Cuartas Micieces, Raul Poler and Josรฉ Antonio Comesaรฑa Benavides from CIGIP-UPV expand on how advanced optimisation techniques can enhance economic, environmental, and social performance across the wood supply chain โ from routing and transport modes to inventory and facility location.
๐ What makes this paper unique?
The authors analysed the multiple optimisation challenges as ๐ข๐ง๐ญ๐๐ซ๐๐จ๐ง๐ง๐๐๐ญ๐๐ ๐๐๐๐ข๐ฌ๐ข๐จ๐ง ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ๐ฌ with trade-offs involved and ๐๐๐ in isolation.
In the second paper, the same authors tackle one of the most complex supply chain challenges โ “๐๐๐๐ข๐ฅ๐ข๐ญ๐ฒ ๐ฅ๐จ๐๐๐ญ๐ข๐จ๐ง” โ using advanced metaheuristics, developing a model to reduce total system costs and improve decision-making in large-scale, dynamic environments.
Within this paper, future directions will include:
โก๏ธIntegrating real-time analytics,
โก๏ธMachine learning, and
โก๏ธMulti-objective optimisation frameworks to enhance adaptability and sustainability in facility location decision-making.
Both the presentations mark the start of R&D efforts for developing the ๐๐๐ ๐๐ฎ๐ฉ๐ฉ๐ฅ๐ฒ ๐๐ก๐๐ข๐ง ๐๐ฉ๐ญ๐ข๐ฆ๐ข๐ฌ๐๐ญ๐ข๐จ๐ง ๐๐ข๐ ๐ข๐ญ๐๐ฅ ๐๐จ๐จ๐ฅ, a key part of our ongoing commitment to sustainable and circular logistics.
๐กWhat will be the added benefit of the Supply Chain Optimisation Digital Tool beyond the project?
โก๏ธCompanies can use this tool to design, simulate, and optimise their supply chain networks for secondary materials by creating virtual representations of their supply chains for the secondary materials providers, recyclers, transporters, formulators and users.