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This study addresses the difficulties associated with inventory management ofproducts with stochastic demand. The objective is to find the optimalcombination of order quantity and reorder point that maximizes profit whileconsidering ethical considerations in inventory management. The ethicalconsiderations are risk assessment, social responsibility, environmentalsustainability, and customer satisfaction. Monte Carlo simulation (MCS) is usedin this study to generate a distribution of demand and lead times for theinventory items, which is then used to estimate the potential profit and riskassociated with different inventory policies. This work proposes a hybridoptimization approach combining Gaussian process regression and conditioningfunction to efficiently search the high-dimensional space of potentialcontinuous review (r, Q) and periodic review (p, Q) values to find the optimalcombination that maximizes profit while considering ethical considerations. Thefindings show that both the (r, Q) and (p, Q) approaches can effectively manageinventory with stochastic demand, but the (r, Q) approach performs better(profits up by 12.73%) when demand is more volatile. The study addsquantifiable risk assessment and sensitivity analysis to these considerations,considering the variation in demand and expected output in profit percentage.The results provide useful information for making ethical and responsiblechoices in supply chain analytics, boosting efficiency and profits.

A Novel Approach with Monte-Carlo Simulation and Hybrid Optimization Approach for Inventory Management with Stochastic Demand