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Scheduling is the process of arranging, controlling and optimizing work and workloads in a production process. Companies use backward and forward scheduling to allocate plant and machinery resources, plan human resources, plan production processes and purchase materials.
Usually a scheduling system based on an optimization software is necessary if the production is executed on machines and it is non-trivial to decide on which machine a specific production order should be executed in order to use resources optimally. Such a type of scheduling problem is known as Job shop scheduling or Flow shop scheduling. Job ...
Backward induction is the process of determining a sequence of optimal choices by reasoning from the endpoint of a problem or situation back to its beginning using individual events or actions. [1] Backward induction involves examining the final point in a series of decisions and identifying the optimal process or action required to arrive at ...
This is contrary to CPM logic, where a forward and backward pass algorithm defaults objects to their early dates, unless additional logic is introduced to constrain an object to a later date. GPM logic permits the as-planned scheduling framework because logic links retain their own attributes, namely gap. [3]
A master production schedule (MPS) is a plan for individual commodities to be produced in each time period such as production, staffing, inventory, etc. [1] It is usually linked to manufacturing where the plan indicates when and how much of each product will be demanded. [2]
Traditional production planning and scheduling systems (such as manufacturing resource planning) use a stepwise procedure to allocate material and production capacity.This approach is simple but cumbersome, and does not readily adapt to changes in demand, resource capacity or material availability.
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Automated planning and scheduling, sometimes denoted as simply AI planning, [1] is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles.
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