A stochastic equilibrium chance-constrained programming model for municipal solid waste management of the City of Dalian, China

In this paper, a stochastic equilibrium chance-constrained programming (SECCP) model was developed for tackling the municipal waste management issue under uncertainty. The main advantage of this model is that it effectively reflected the dual-random characteristics of uncertain parameters through incorporating the opinions and judgments from various respondents into the parameter identification processes. This will lead to birandom variables, where their mean values and standard deviations are allowed to be the random variables, instead of the fixed values. The generation of birandom variables will enrich the stochastic optimization theory and improve the accuracy and rationality of parameters design and estimation. The equilibrium chance-constrained programming algorithm was used to solve the SECCP model, which is capable of tackling birandom variables and is overcoming limitations of traditional stochastic chance-constrained programming while parameters with normal distribution are required strictly. Currently, the application of SECCP model in the environmental management fields was limited. As the first attempt, the regional waste management of the City of Dalian, China, was used as a study case for demonstration. A variety of solutions are beneficial in providing decision space to the local managers through designing and adjusting the constraints-violation levels. This solution process also reflected trade-off between system economy and reliability. The successful application in regional waste management system is expected to be a good example for tackling other similar problems.