Reliability-based decision making for selection of ready-mix concrete supply using stochastic superiority and inferiority ranking method

• This study models decision aiding method to assess ready-mix concrete unloading type.
• Applying Monte Carlo simulation to virtual-scale method achieves a reliable process.
• Individual preference ranking method enhances the quality of global decision making.
• Robust stochastic superiority and inferiority ranking obtains reasonable results.

Corporate competitiveness is heavily influenced by the information acquired, processed, utilized and transferred by professional staff involved in the supply chain. This paper develops a decision aid for selecting on-site ready-mix concrete (RMC) unloading type in decision making situations involving multiple stakeholders and evaluation criteria. The uncertainty of criteria weights set by expert judgment can be transformed in random ways based on the probabilistic virtual-scale method within a prioritization matrix. The ranking is performed by grey relational grade systems considering stochastic criteria weight based on individual preference. Application of the decision aiding model in actual RMC case confirms that the method provides a robust and effective tool for facilitating decision making under uncertainty.