ScienceDocs · Operations research & decision support
Optimization Engineering Services
Turn complex decisions into workable plans.
Use mathematical modeling, simulation, and AI where useful to improve scheduling, routing, inventory, and resource allocation. Our specialists connect rigorous analysis with the realities of your operations.
Clear objectives. Explicit constraints. Practical decisions.
The people behind the models
Meet your optimization team
Explore the specialists, then tell us what your organization needs to improve.
Mr. Kraus
Technical Program Director
Connects optimization, AI, software engineering, and technical program delivery with operational and commercial priorities.
Dr. Shi
Inventory & retail optimization
Develops large-scale models for inventory placement, replenishment, pricing, and promotion decisions.
Dr. Michael
Scheduling & network optimization
Builds production-ready decision systems for aviation, workforce scheduling, supply chains, and warehouse operations.
Dr. Mohammad
Analytics & simulation
Combines optimization, simulation, and machine learning for planning, scheduling, and operational decision support.
Dr. Jerry
Logistics & transportation
Applies routing, scheduling, and simulation to logistics, manufacturing, supply-chain resilience, and workforce planning.
Dr. Hossein
Supply chains & decision systems
Develops optimization software for network design, production planning, scheduling, and decisions under uncertainty.
Dr. Zhu
Large-scale optimization
Builds scalable mixed-integer and stochastic models for networks, logistics, maintenance, and real-time decisions.
Dr. Arash
Smart & sustainable logistics
Models last-mile delivery, collaborative routing, and tradeoffs among cost, time, reliability, and emissions.
Where we help
Different operations. Better-informed decisions.
Logistics & transportation
Routing, fleet planning, and supply networks.
Healthcare, biotech & clinical operations
Staffing, patient flow, and research resources.
Energy & industrial systems
Capacity, investment, and process decisions.
Manufacturing & operations
Production, inventory, and workforce scheduling.
Aerospace, defense & government
Mission planning, readiness, and resource allocation.
Technology & data-driven enterprises
Algorithms, product features, and decision engines.
From question to implementation
A model is useful when people can use it.
01
Define
Agree on the decision, constraints, data, and success measures.
02
Model
Build and compare suitable optimization or simulation approaches.
03
Validate
Test assumptions and scenarios with the people using the results.
04
Implement
Support deployment, handoff, and refinement against agreed goals.
Methods may include mixed-integer programming, heuristics, simulation, and machine learning. The problem determines the tools.
See the team’s project experience.
Explore examples across scheduling, logistics, and supply-chain optimization.
Connected expertise
When the challenge goes beyond a model.
Bring AI readiness, employee adoption, and cybersecurity into the scope where needed. For Los Angeles businesses, Civoryn brings these disciplines together.
What decision should work better?
Start with a no-cost exploratory conversation about your operations and priorities.