The remaining sections of this paper are organized as follows. Thus, two improved particle swarm optimizations (i.e., NS-PSO and NIW-PSO) are proposed for the dynamic flexible flow shop problem. Furthermore, due to the fact that dynamic scheduling problem is well known as NP-hard, different methods are employed to solve the scheduling problem. A dynamic scheduling strategy based on predictive-reactive scheduling approach is adopted to represent the multi-objective optimization problem.

In this paper the energy consumption and makespan are analyzed while considering dynamic factors in the flexible flow shop.

However, uncertain events, such as new job arrivals and machine breakdown are not taken into consideration. Some general multi-objective scheduling models to minimize makespan and energy consumption have proven to be effective in the flexible flow shop. It is evident that the previous static decision-making models of scheduling problems have some severe limitations for real production environments. However, scheduling problems are dynamic in nature and complex due to uncertain events occurring in real-world production scheduling. Only few works, are focused on reactive approaches for sustainable operations scheduling. Most of these research works are primarily concerned with developing a mathematical model for solving the static scheduling problem.

Recently, many interesting efforts have been performed to investigate production-scheduling problems that take into account energy efficiency. Besides, from the manufacturing system-level perspective, optimizing the objectives of production scheduling is a feasible and efficient approach for manufacturing companies to decrease energy consumption without any machine or product redesign. Research on reducing the energy consumption of manufacturing processes has mainly focused on the energy consumption optimization based on the machine level and the product level, respectively, ,. An important aim of manufacturing companies is to reduce energy consumption for cost-saving and environment-friendly modes in terms of the development of sustainable manufacturing. Nowadays manufacturing industry is facing the enormous environmental challenge as well as strong economic pressure due to the increasing energy requirements and associated environmental impacts.

Particle shop