Hybrid Simulation

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Hybrid Simulation Optimization for Navy
Manpower Planning and DistributionDouglas A.
Samuelson, Steven P. Wilcox, Paul Thornton
Navy Manpower Planning ConferenceArlington, VA
6 May 2008
Serco, IncBUPERS-11N00189-04-D-0007-7J50
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Introduction

• Background
• ONR-sponsored via Capable Manpower ACQUIRE
  program at NPRST
• Final phase of Distribution Incentive System
  (6.3) research
• Purpose
• Model current Enlisted distribution system
  business rules and policies
• Incorporate alternative paradigms for
  distribution and assignment of Enlisted personnel
• Optimized assignments
• Demand-driven vice supply-driven requisitions
• Test and compare how variations in policy and
  paradigm affect manning, sea-shore rotation, and
  other metrics of interest

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Hybrid Simulation Optimization for Navy
Manpower Planning and DistributionOverview

• Task Requirement
• Develop model that baselines the current
  distribution system and various implementations
  of future systems over an extended period of time
• Simulate the current distribution system
• Stimulate proposed system with policy inputs
  (user controlled)
• Provide capability to vary selected policies
• Produce metrics on Navy manpower utilization
• Integrated data/modeling system
• Computer software product end items
• Software users manual
• Technical Report / Study / Analysis Support
  Services

• Task Result/Usage
• Model that
• Baselines the existing distribution system and
  policy parameters
• Enables analysis of proposed enlisted
  distribution policies and requirements across
  time
• Allows for graphical depiction of manpower
  utilization and other manpower metrics

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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Important
Functions and Capabilities

• Documented current capability
• Project inventory (distributable and
  non-distributable)
• Develop allocation control to MCA
• Develop manning control (NMP) based on levers
• Develop assignment control
• Developed model to wargame proposed capability
• Set and analyze impact of policy levers on
  manpower utilization over time
• Generate manpower metrics
• Retain scenarios for comparison
• Objectives
• Fill a higher proportion of high-priority
  billets
• Reduce the number of misfits
• (placements above or below current skill
  level)

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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Data Testing

• Data Requirements
• Individual enlisted classification and
  qualification data (EMF)
• Historical distribution outcomes (EMF)
• Force structure information (historical and
  future)
• History of relevant policy lever settings (such
  as accession mix, promotion timing, sea-shore
  rotation, MCA prioritization, grade substitution,
  etc)
• Testing/Verification
• Baseline development tied to current methodology
• 2-spiral development with increase in complexity
  and policy variables
• Test cases to support integration of features and
  modeling components being incorporated
• Integrity of implementation of equations
• Verification and Validation
• Behavioral analysis of the model under use
• Joint review and analysis with Navy enlisted
  strength planners,
• Comparisons of test cases with existing systems
  and baseline system

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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Approaches
Considered

• Markov Chain analytical models
• Get exact calculations
• Some assumptions inappropriate (uniformity of
  transition rates)
• Can overwhelm computational capacity high
  number of states, transitions
• Discrete-event simulation
• Straightforward, easily implemented
• Assumes few if any interactions among
  individuals, groups
• Agent-based simulation
• Handles interactions among individuals, groups,
  skill classes
• Capable of features difficult to imnplement and
  beyond scope of current task
• Microsimulation
• Ideal for modeling an aging population age
  increases are exact, automatic
• Has advantages of Markov Chain analytical models,
  more tractable
• Not yet used for manpower planning hard to find
  good software for this
• (best was CoMicSim, TU-Koblenz not documented
  in English yet)

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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Approach
Adopted

• Discrete-event simulation with agent-based
  capability
• Java-based, interfacing to MASON (ABS package
  from GMU)
• Assumes no interactions among individuals, groups
  but could handle
• Could readily be adapted to full microsimulation
• Simulation projects available manpower by skill
  set, for specified years
• User can specify up to 15 years, whatever EMCs
  are desired
• Projects available, attrition, promotions using
  pre-specified rates
• No interaction between simulation and
  optimization
• Optimization handles assignments for each year
• Typical assignment problem with prioritization of
  infeasibilities
• User can adjust specification of objectives /
  priorities and rerun as desired

Easy to use and interpret Faithful to actual
situation Easy to maintain, upgrade and extend
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Initial Screen
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Add New
Scenario
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Edit Scenario
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Specify
Policies for Filling Positions
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Specify
Policies Detail (Pay Grade Substitution)
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Specify
Policies Additional Detail (Pay Grades)
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Specify
Assignment Policy
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution View Billets
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution View Inventory
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution View
Inventory Detail
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Configure
Rates
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Reports Menu
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Hybrid Simulation Optimization for Navy
Manpower Planning and Distribution Conclusions

• SimOpt provides
• A framework to expand the rules within the
  requisition and assignment modules
• Ability to add rules and enhancements to the
  simulation of the inventory
• Reports and metrics describing the results from
  the simulation
• Recommended next steps
• See how well the model tracks actual events
• Note suggestions for improved utility, ease of
  use
• Expand and improve the requisition process
• Improve ultimate assignments
• Take group effects, interactions among EMCs into
  account
• Incorporate interactions between assignments and
  future availability
• Incorporate responsiveness to changing external
  conditions
• The authors gratefully acknowledge the support
  and guidance of the Office of Naval Research
  (ONR) and Navy Personnel Research, Studies and
  Technology (NPRST).