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Multi-objective Queueing Simulation

Multi-objective queueing simulation combines discrete-event queueing models with multi-objective optimization to simultaneously evaluate and optimize conflicting performance metrics — such as average wait time, server utilization, throughput, and service cost — across a simulated queuing system. It produces a Pareto front of non-dominated solutions rather than a single optimal point, enabling decision-makers to understand trade-offs explicitly.

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Multi-objective Queueing Simulation — Simultaneous optimization of competing performance metrics in simulated queuing systems

Taksonomisk metoderegistrering · process-pipeline / simulation

Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Pearson Prentice Hall. · ISBN 9780136062127
Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons. · ISBN 9780471873396

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Same method familyDiscrete-Event Simulationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-objective discrete-event simulationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-Objective Optimizationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketQueueing Simulationmachine-suggested · Relational suggestion, not evidence.