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Due to its practicality, hybrid flowshop scheduling problem (HFSP) with productivity objective has been extensively explored. However, studies on HFSP considering green objective in distributed production environment are quite limited. Moreover, the current manufacturing mode is gradually evolving toward distributed co-production mode. Thus, this paper investigated a distributed hybrid flowshop scheduling problem (DHFSP) with objectives of minimization the makespan and total energy consumption (T E C). To address this problem, this paper designed a Pareto-based multi-objective hybrid iterated greedy algorithm (MOHIG) by integrating the merits of genetic operator and iterated greedy heuristic. In this MOHIG, firstly, one cooperative initialization strategy is proposed to boost initial solutions' quality based on the previous experience and rules. Secondly, one knowledge-based multi-objective local search method is invented to enhance the exploitation capability according to characteristics of problem. Thirdly, an energy-saving technique is developed to decrease the idle energy consumption of machine tools. Furthermore, the effectiveness of each improvement component of MOHIG is assessed by three common indicators. Finally, the proposed MOHIG algorithm is compared with other multi-objective optimization algorithms, including SPEA2, MOEA/D, and NSGAII. Experimental results indicate that the proposed MOHIG outperforms its compared algorithms in solving this problem. In addition, this research can better guide practical production in some certain environments. • Considering green scheduling in distributed hybrid flowshop environment. • Designing a new energy-saving strategy into this problem. • Proposing a Pareto-based multi-objective hybrid iterated greedy algorithm (MOHIG). • Evaluating performance of the proposed MOHIG by conducting comparison experiments. [ABSTRACT FROM AUTHOR]

• Two seasonal-regulatable solar energy utilization systems have been proposed. • Comprehensive performance is greatly enhanced via multi-objective optimization. • Solar year-round effective utilization period can be enhanced by 2.63-fold. • The investment is dramatically reduced by over 70% under the same conditions. Space heating via fossil energy accounts for tremendous energy consumption and carbon emissions. Solar energy has enormous potential for building space heating in the heating season, but the more abundant solar resource is often in excess during the non-heating season, which leads to vast seasonal residual solar energy being wasted. In this paper, two solar seasonal-regulatable energy systems are proposed to solve this problem, i.e., System A: solar thermal and photovoltaic integration, and System B: solar thermal incorporating the organic Rankine cycle. Both systems are aimed at regulating the year-round solar energy for space heating in the heating season and making full use of solar seasonal residual energy for electricity generation in the non-heating season. The results show that the two systems can improve the effective solar utilization efficiency by 69.12% and 18.65%, respectively, and both can enhance the solar effective utilization period by 2.63-fold over the conventional solar thermal system. Besides, in comparison to the actual solar seasonal storage system monitoring data, both systems will dramatically decrease the investment cost by 72.69% and 72.22%, respectively. Overall, the superiority of solar seasonal-regulatable energy management systems in district-level applications is proven and it is instrumental in achieving the decarbonization goal. [ABSTRACT FROM AUTHOR]