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This paper proposes a modal interval based genetic algorithm to solve the closed-loop supply chain network configuration puzzle under uncertainty.
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All estimates were within the expected interval based on bootstrapping.
Appointment dynamics are often deeply related to interval based reward schedules or avoidance dyanmics.
Definition: Interval based reward schedules provide a reward after a certain amount of time.
Businesses remit this at intervals, based on size.
In this paper a new approach to the solution of continuous minimax problems over reals is introduced, using tools based on modal intervals.
They can be estimated by modal interval analysis.
This paper applies the modal intervals to characterize the uncertain parameters and combine the modal interval analysis with the genetic algorithm to solve the proposed modal interval linear programming problem.
In this paper, the modal interval analysis method to estimate modal parameters, frequency response function (FRF), and mode shapes of structures with uncertain-but-bounded is presented.
Here we will present briefly Halpern and Shoham's propositional modal interval logic, hereafter called \(\mathsf{HS}.\) It employs a set of unary modal operators corresponding to each of Allen interval relations and having Kripke semantics over that relation.
Integrating modal interval arithmetic [ 46] in the proposed framework might be a possible option, under research at this moment.
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