Optimizing green production strategies: An integrated approach

• GP strategy is optimized by analyzing trade-off between production economy and green yield.
• An integrated solution approach combining simulation with evolutionary optimization is proposed.
• Simulation represents system and evaluates solutions under dynamic and uncertain conditions.
• Modified genetic algorithm is used to find better solutions via random and swarm search.
• Model designs are robust and flexible based on experimental results and sensitivity analyses.

Selection of green production strategy is a critical but difficult task due to the fact that it affects not only green benefits, but also production economy. The problem is essentially multi-objective and involves dynamic and uncertain conditions. This study focused on an integrated approach to improve the analysis and facilitate decision-making process. Discrete-event simulation model was developed to capture production flow and decision logic under real world conditions. A multi-objective genetic algorithm (MOGA), combined with improving heuristics, was developed to search the best solutions (Pareto optimums). The two modules are integrated to work in evolutionary cycles to achieve the optimization. Experiments were designed and carried out via a prototype system developed to verify and validate proposed concepts, including sensitivity analysis of related model parameters.