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CAP-SCHED

Financiado

Cerrado

Competitive Advantage for Process intensive industries by SCheduling with Heuris...

Competitive Advantage for Process intensive industries by SCheduling with Heuristics EnhanceD simulation optimisation A competitive weapon for companies in process-intensive industries such as the chemical industry, is effective mastery of supply chain management from raw material to end product so as to improve efficiency, effectiveness, & profi... ver más

31/03/2011

Princeps

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

PRINCEPS SARL No se ha especificado una descripción o un objeto social para esta compañía.

Fecha límite participación Sin fecha límite de participación.

Ver 6 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2011-03-31 No tenemos la información de la convocatoria

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

6 Participantes

Princeps

423.78K€ | Lider

HoGent

N.D. | Participante

INSTITUT MINESTELECOM

N.D. | Participante

MANOPT

N.D. | Participante

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Líder del proyecto

PRINCEPS SARL No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto A competitive weapon for companies in process-intensive industries such as the chemical industry, is effective mastery of supply chain management from raw material to end product so as to improve efficiency, effectiveness, & profitability. However, in flow scheduling, the human operator can be overwhelmed by the complexity of the problem. CAP-SCHED involves developing a new intelligent scheduling system for companies in continuous/semi-continuous process industries. The innovative solution uses a multi-agent framework to combine 2 existing approaches which, individually, are inadequate to improve scheduling. However, combining both approaches offers significant improvements to implement more profitable solutions to scheduling problems, with better account taken of constraints. The 2 approaches are: 1. Simulation through trial & error: * The scheduler instructs the system to calculate all material flows in terms of quantity & quality from up- to down-stream throughout the plant; * If infeasibility occurs (e.g. capacity limitation…) then the planner readjusts parameters in trial & error mode to reach a feasible solution. and 2. Algorithmic constraint solving: * the problem is represented as a mathematical model & the system attempts a solution, helped by heuristic guesses so as to guide the search algorithm via domain knowledge. The new idea is to allow full interaction with the system via a Graphical User Interface as if running in simulation mode, & to translate instructions, when the value of an operating parameter (or the starting date of an event…) is fixed, in terms of constraints imposed in the mathematical model. Thus, the person responsible for scheduling can choose to fix variable values, and to let the system find those left free so as to reach a feasible solution. Overall, the solution will drastically reduce the need for multiple planning/scheduling loops so as to achieve a consistently optimised solution with improved profitability.

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