ABSTRACT Rooted from the Industry 4.0 principles, Cloud Manufacturing (CMfg) is a novel customer-oriented manufacturing norm, which can assist enterprises to withstand in the nowadays highly volatile and competitive market. CMfg systems comprise two separate parties, namely, customers and factories, with independent individuals. In this regard, considering the utilities of both customers and factories and establishing the equity amongst their individuals are of particular importance for the survival and flourishment of CMfg systems. Furthermore, due to the limited capacity of resources, tightness of due dates, and customers’ cost expectations, all orders may not be accepted in CMfg systems. Accordingly, this paper aims to explore a scheduling problem in a CMfg system. A multi-objective mathematical model is presented for the problem, which can determine the acceptance or rejection of orders, set prices, and schedule them in an integrated manner to maximise the customers and factories’ utilities, and enhance the equity among their members. Due to the high complexity of the problem, two matheuristic methods based on the Multi-Objective Grey Wolf Optimizer (MOGWO) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) are developed. An extensive computational experiment is carried out to validate the proposed matheuristic methods and evaluate their performance. Moreover, some guidance is presented for managers by conducting a sensitivity analysis.