A multi-modal immune algorithm for the job-shop scheduling problem

Baldwinian learning in clonal selection algorithm for optimization

“…Some of the first work in applying immune system paradigms was undertaken in the area of fault diagnosis [25]. Later work applied immune system paradigms to the field of computer security [13,27,38], which seemed to act as a catalyst for further investigation of the immune system as a metaphor in many areas, such as anomaly detection [20,40], pattern recognition [3,6,41], and optimization [8,10,11,[17][18][19]28,29,36,42,46]. The first immune optimization algorithm may be the work of Fukuda et al [15] that included an abstraction of clonal selection to solve computational problems [16].…”

Some single-machine and m-machine flowshop scheduling problems with learning considerations

“…In classical scheduling theory, it is assumed that the job processing times are fixed and known from the first job to be processed to the last job to be completed ( [13,20,[23][24][25]). However, recent empirical studies in several industries have demonstrated that unit costs decline as firms produce more of a product and gain knowledge or experience.…”

Parallel bat algorithm for optimizing makespan in job shop scheduling problems

“…The objective of this paper is to minimize makespan. In recent years, an interest in using meta-heuristic methods to solve JSSP has been growing rapidly, such as simulated annealing (SA;Laarhoven et al 1992;Song et al 2012), tabu search (TS; Dell'Amico and Trubian 1993; Geyik and Cedimoglu 2004;Zhang et al 2007), genetic algorithms (GA; Davis 1985;Moin et al 2015;Gonçalves et al 2005;Cheng et al 1996), particle swarm optimization (PSO; Lian et al 2006;Lin et al 2010), artificial immune system and their hybrids (AIS; Coello et al 2003;Qiu and Lau 2014;Luh and Chueh 2009;Zhang and Wu 2010), discrete artificial bee colony (DABC; Yin et al 2011), discrete imperialist competitive algorithm and hybrid imperialist competitive algorithm . These approaches comprise the emergence of promise for conquering the combinatorial exploration in a variety of decision-making arenas.…”