## 1 Introduction
These approaches cannot consider the scheduling and layout planning problems from the perspective of system optimization and ignore their interaction, which may prevent improvement of the productivity and energy efficiency of the manufacturing system and generate the following problems:  
* In much research, scheduling is done based on the assumption that the transportation time between machines is either neglected or determined. However, in the actual workshop, the positions of machines will significantly affect the transportation time of jobs. This may make the enterprises' production cycle longer or generate production stagnation, which leads to more idle energy consumption. Therefore, the generated scheduling schemes are somehow unrealistic and cannot be readily executed in the workshop, resulting in the optimum scheduling scheme often becoming infeasible;
* After the layout is set, the performance of scheduling schemes is highly dependent on the determined layout scheme. Moreover, if the type and requirement of the product change greatly, the scheduling scheme will change accordingly. As a result, the material handling information between machines will be greatly affected, which may cause the original layout scheme to become inefficient;
* Separate optimization of scheduling and layout planning does not guarantee optimality of the whole manufacturing system since scheduling or layout planning has more than one criterion to be considered, in which many criterions are often conflicting. For example, in the real manufacturing process, each operation could be implemented on a set of machines, including dedicated machines and universal machines. Generally, when an operation is processed on the dedicated machine, the corresponding processing time and energy consumption are minimal. In this manner, the scheduling scheme displays a short completion time and low processing energy consumption, while the corresponding layout scheme may lead to high transportation energy consumption and material handling quantity since the jobs are frequently transported between machines. On the contrary, the scheduling scheme may lead to a long completion time and high processing energy consumption, while the corresponding layout scheme may lead to low transportation energy consumption and material handling quantity. Neither of these manners can obtain a high production efficiency and low energy consumption solution. The above problems can be conquered by the integration of scheduling and layout planning (ISLP), which has been a hot research topic in recent years. [PERSON] et al. (2018) studied a concurrent layout and scheduling problem in a job shop environment to minimize makespan. [PERSON] et al. (2018, 2019) developed a multi-objective mathematical model for integrated job shop scheduling and the facility layout planning problem that considers makespan, mean flow time, material handling cost, and closeness rating score simultaneously. [PERSON] (2018) proposed a flexible batch scheduling problem which was integrated with loop layout pattern design, and applied the genetic algorithm (GA) and simulated annealing algorithm (SA) to solve the problem for minimizing makespan and transportation cost. [PERSON] et al. (2018) studied an integrated optimization problem of workshop layout and scheduling considering energy consumption to minimize makespan and carbon emission simultaneously, in which they proposed a multi-objective fruit fly optimization algorithm to solve the problem. Besides this, in the field of cellular manufacturing, [PERSON] et al. (2018), [PERSON] et al. (2018), and [PERSON] et al. (2018) studied the integrated cell formation, group layout, and group scheduling, and applied GA to solve the problem for minimizing makespan. [PERSON] et al. (2018) adopted the multi-objective genetic algorithm (MOGA) for the cell formation problem considering cellular layout and operation scheduling to minimize makespan and transportation cost. [PERSON] et al.