## 2 Related Work  
Currently, many scholars or teams have been studying the RSCA problem. Among them are: (1) [PERSON], [PERSON], and [PERSON] in Osaka, Japan; (2) [PERSON] in Sweden; (3) [PERSON] in Britain; and (4) some scholars in China, such as [PERSON], [PERSON], [PERSON] and [PERSON]. They have proposed various algorithms for solving the static or dynamic RSCA problems and extended ones by adding modulation formats or core modes when considering crosstalk or core switching. For dynamic network scenarios, existing works [13; 14; 15] have studied the spectrum fragmentation problem in dynamic resource allocation. Specifically, [PERSON]. [13] proposed a crosstalk-aware spectrum defragmentation algorithm based on the spectrum compactness metric. To reduce crosstalk and spectrum fragmentation, [PERSON]. [14] investigated an RSCA algorithm based on spectrum partition, predefined core priority, and classification. To make full use of spectrum resources and minimize spectrum fragments, [PERSON]. [15] proposed a multi-core virtual connection scheme considering inter-core crosstalk to construct super-channels in the dimensions of core and spectrum. Aiming at using the frequency slot allocation patterns (FSAPs) with the least amount of wasted FSs and exploiting path diversity [16], a set of new algorithms is proposed. For the static RSCA problem, many works have investigated heuristic or intelligent algorithms. [PERSON]. [2] proposed several versions of a greedy algorithm based on different demand order strategies for solving the routing, space (i.e., optical fiber, core or mode), and spectrum allocation problems, in which inter-core crosstalk is not considered. [PERSON]. [5] studied the RSCA problem with the impairments and security vulnerabilities caused by inter-core crosstalk, specifically, in which the trust of some nodes in the network is lower than that of other nodes. The authors formulated an integer linear programming (ILP) model that optimizes spectrum utilization and crosstalk simultaneously and designed a corresponding heuristic algorithm. To study the anycast RSCA problem, [PERSON]. [6] established an ILP model that considers inter-core crosstalk to minimize the Maximum FS Index (MFSI, as defined in [7]) of an EON, and then proposed a heuristic algorithm that mainly uses the shortest path first algorithm and the predefined core priority crosstalk reduction technique to solve the established model, in which core switching is not considered. Ref. [17] proposed a programmable architecture on demand (AoD) node, which can provide a more flexible and scalable architecture for multi-dimensional switching including core switching, and studied the RSCA problem considering the modulation format under quasi static traffic scenarios in SDM-EONs. To overcome the drawbacks in Ref. [2] and Ref. [6], [PERSON], et al. [8] studied the RSCA problem by considering both inter-core crosstalk and core switching. The authors first analyzed three crosstalk constraint methods: XT-avoid, XT-WC and XT-aware, where XT denotes crosstalk and only XT-aware strictly considers the crosstalk FSs between adjacent cores. They established a hybrid ILP model to minimize the MFSI and proposed a heuristic algorithm with crosstalk awareness. Particularly, it calculates K-shortest paths (KSPs) for each connection request in advance, and then allocates routing, cores, and spectrum resources that meet the constraints of the spectrum and inter-core crosstalk for all requests. Different from all the mentioned references that use heuristic algorithms for solving the RSCA problem, Refs. [9; 10; 11; 12] proposed a corresponding intelligent algorithm that is based on some optimization and guidance mechanisms, and the obtained solutions are better than those resulting from heuristic algorithms. Concisely, these articles first established the mathematical model of the RSCA problem, then designed a reasonable chromosome coding scheme, and finally used a genetic algorithm to evolve the population to obtain the optimal solution. In these studies, only Ref.