LAUSR

Abstract In recent years, coal power has obvious advantages in terms of safety, economy and stability. As people gradually realize the importance of the environment, low carbon has become one of the core indicators of power system evaluation, so it is particularly important to guide the coal enterprises to achieve a win-win situation of economic and environmental benefits. Combined with the carbon emission policies, this paper takes the coal supply chain network as the research object and aims to develop a comprehensive decision model for sustainable design of coal supply chain. First, this paper extracts the influencing factors of low-carbonization in coal supply chain and constructs an interpretative structural model (ISM). The results show that low-carbon green technology, low-carbon production cost, utilization level of green energy and energy efficiency are the most basic manifestations of low-carbonization of coal supply chain and interact with each other, therefore this paper builds an optimization model with the objective of minimizing the low-carbon production costs in the coal supply chain. Concurrently, this paper introduces four policies (emission cap, carbon tax, carbon trade and carbon offset) as constraint condition. Then, in the aspect of model solving, this paper combines the differential evolution (DE) strategy to mutate, cross and select the leaders generated in each iteration of the salp swarm algorithm (SSA), further increases the diversity of the salp swarm, avoids the algorithm falling into a local optimum, and proposes the salp swarm algorithm based on differential evolution (DE-SSA). Finally, this paper compares the effects of four different carbon emission policies on the optimization of coal supply chain network through empirical analysis, and finds that coal enterprises have the best emission reduction effect under the carbon trade policy. The development and implementation of this paper not only enriches the related research of efficient supply chain, but also provides scientific and quantifiable decision-making technology for coal enterprises.