A scenario-based robust optimization model for the sustainable distributed permutation flow-shop scheduling problem

Keyphrases

• Robust Optimization 100%
• Distributed Permutation Flowshop Scheduling 100%
• Scenario Optimization 100%
• Adaptive Large Neighborhood Search 75%
• Numerical Examples 50%
• Production System 50%
• Search Space 50%
• Energy Consumption 50%
• Flow Shop 50%
• Parameter Optimization 25%
• Sensitivity Analysis 25%
• Heuristic Algorithms 25%
• Complex Optimization Problems 25%
• Job Opportunities 25%
• Parameter Calibration 25%
• Economic Criteria 25%
• Current Solution 25%
• Local Search Algorithm 25%
• Different Operating Modes 25%
• Scenario Approach 25%
• Environmental Criteria 25%
• Social Criteria 25%
• Machine Breakdown 25%
• Constructive Heuristic 25%
• Working Day 25%
• Computational Study 25%
• Sustainable Production Scheduling 25%
• Lost Workdays 25%
• Workdays Lost 25%
• Multiple Uncertainties 25%
• Random Arrival 25%
• Probabilistic Scenarios 25%
• Exact Solver 25%
• Variable Processing Times 25%
• Expected Makespan 25%
• Construction Heuristics 25%

Computer Science

• Scheduling Problem 100%
• Flowshop Scheduling 100%
• Robust Optimization 100%
• Search Space 50%
• Energy Consumption 50%
• Adaptive Large Neighborhood Search 50%
• Numerical Example 50%
• Production System 50%
• Optimization Problem 25%
• Metaheuristics 25%
• Production Scheduling 25%
• Adaptive Large Neighborhood Search Algorithm 25%
• Metaheuristic Algorithm 25%
• Processing Time 25%
• Local Search Algorithm 25%
• Construction Heuristic 25%
• Operating Mode 25%

Engineering

• Flowshop Scheduling 100%
• Production System 50%
• Search Space 50%
• Numerical Example 50%
• Search Algorithm 50%
• Search Neighborhood 50%
• Optimisation Problem 25%
• Optimality 25%
• Operating Mode 25%
• Processing Time 25%
• Local Search 25%
• Depth Discussion 25%
• Sustainable Production 25%