Visy Selects SolveIT Software for Supply Chain Network Optimisation

World's largest privately owned packaging, paper and recycling company, Visy, will optimise multi-plant order allocation schedules using SolveIT Software's Supply Chain Network Optimisation (SCNO) system.

Adelaide, South Australia (PRWEB) October 29, 2008 -- SolveIT Software Pty Ltd, a leading provider of enterprise software solutions for supply & demand optimisation and predictive modelling, announced today it has signed a contract with Visy for piloting SolveIT Software's Supply Chain Network Optimisation (SCNO) system across Visy's pulp & paper division.

Designed to enable company-wide (globally) optimised decisions, rather than silo-based (locally) optimised decisions, SolveIT Software's SCNO system will be piloted by Visy Pulp & Paper to optimise multi-plant production order planning. Visy Pulp & Paper currently produces recycled corrugated paper for the packaging & building industries from six 100% recycled machines in Australia, located in Melbourne, Sydney and Brisbane. Together, these machines produce approximately 700,000 tonnes of packaging paper each year. By taking into account customer demands, plant characteristics and capacities, and costs and modes of transport, SolveIT Software's SCNO system will generate optimised multi-plant order allocation schedules.

Headquartered in Melbourne, Australia, Visy is the world's largest privately owned packaging, paper and recycling company. For more information about Visy, please visit www.Visy.com.au
   
"We look forward to adding value to Visy's operation by providing decision support on where to produce and ship products," said Dr. Zbigniew Michalewicz, Chairman of the Board of SolveIT Software. "Based on leading advances in optimisation and decision support technologies, SolveIT Software's Supply Chain Network Optimisation system allows for analysing constraint violations and trade-offs on supply chain activities, optimising contingency plans, and conducting financial-based what-if analysis and scenario comparison."

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