How to deal with the key contradiction between mass production effects and customised demand is the key problem of mass customisation (MC) (Pine II 1993, Silveira et al. 2001). In this aspect, postponement has been widely used by many scholars (for example, Ma et al. 2002, Jiao et al. 2003, Li et al. 2007, Shao and Ji 2008, Brun and Zorzini 2009, among others). The core of postponement is to delay the customer order decoupling points (CODP) (Gu et al. 2002). However, to realise postponement there must be a flexible supply chain system, especially a flexible and efficient supply chain scheduling (SCS) system to give support (Yao and Liu 2009). SCS in MC is complicated and has its own special characters mainly reflected in two aspects. One is the random information from customer orders and the complex relations among supply chain co-operators, which can cause many complicated contradictions in scheduling and bring dynamic or stochastic characteristics to it; the other is the outstanding relations of collaborative benefits and risks in this complicated environment. Therefore, we must probe the ways to respond to these characteristics and analyse the collaborative benefits and risks in MC. In our early work, we focused on how to alleviate the dominant contradictions to solve the dynamic and stochastic problems (Yao and Liu 2009), but we did not pay great attention to the collaborative benefits and risks which are also important factors that lead to the dynamic and stochastic characteristics in SCS. Based on earlier achievements, this paper introduces the collaborative benefit and risk analysis into SCS and emphasises it not only for short-term collaboration but also for long-term collaboration. Then the paper sets up a multi-objective optimisation model and an algorithm to describe the scheduling optimisation of co-operator selection and task allocation in SCS by introducing the collaborative benefits and risks with their judgment methods