Immune clonal selection algorithm for capacitated arc routing problem

An updated annotated bibliography on arc routing problems

“…The results obtained depend on the transformation used so that instance dimension does not increase too much. Recently, Foulds et al [87] propose a compact transformation, ensuring the number of nodes in 27,28,40,41,42,55,87,128,129,138,139,140,142,143,157,160,161,174,178,191,194,195,200] With split deliveries -an edge demand can be serviced by several vehicles [29] Multi-compartment vehicles (MCV) -tasks have a demand for different products and are serviced by MCV [150] Multi-compartment vehicles; Multi-days; Semi-Periodic; With/without split deliveries; Coordinated vehicles…”

“…Recently, Shang et al propose another metaheuristic, more precisely, an immune clonal selection algorithm. This algorithm is inspired by the clonal selection theory, which is proposed to account for the behavior and capabilities of antibodies in the acquired immune system.…”

Immune clonal algorithm based on directed evolution for multi-objective capacitated arc routing problem

“…Compared with other algorithms, the immune clonal algorithm has advantages on quick convergence and global optimization [25,30]. The immune clonal algorithm uses a heuristic algorithm to generate an initial antibody population, and then evaluates the fitness of the initial antibodies and determines the clonal ratio of the antibodies by calculating the affinities between antibodies and antigens [31]. Next, the immune clonal algorithm performs immune gene operations including gene recombination and gene mutation.…”

“…Because the calculation of affinities is very complex, the calculation of antibody clonal ratio is also complex, especially when solving large-scale CARP. From the literature [31], we can see that when the immune clonal algorithm is used for solving the CARP, the ratio of clone is set as 3 which helps increase the antibody's diversity and promotes good performance under the premise of the lower computational cost. Therefore, we directly clone the non-dominant solutions in the initial population at the ratio 3 in order to guarantee the speed and the simple calculation of DE-ICA, and then the clonal individuals are added into the initial population.…”

Optimization on Black Box Function Optimization Problem

“…Immune optimization algorithm (IA), a vital research and promising direction of Artificial Immune System (AIS), is a novel population-based intelligent algorithm based on the theoretical immune principles [20] inspired by adaptive immune system. Due to the advantages of simplicity and ease of implementation and the remarkable optimization capability, IA and its variants have attracted the attention of researchers and have been widely exploited to solve a great variety of related engineering optimization problems [19,[21][22][23][24][25].…”