A New Approach to Solve Flowshop Scheduling Problems By Artificial Immune Systems

Orhan ENGİN, Alper DÖYEN

Öz


The n-job, m-machine flow shop scheduling problem is one of the most general job scheduling problems. This study deals with the criteria of makespan minimization for the flow shop scheduling problem. Artificial Immune Systems (AIS) are new intelligent problem solving techniques that are being used in scheduling problems. AIS can be defined as computational systems inspired by theoretical immunology, observed immune functions, principles and mechanisms in order to solve problems. In this research, a computational method based on clonal selection principle and affinity maturation mechanisms of the immune response is used. The operation parameters of meta-heuristics have an important role on the quality of the solution. Thus, a generic systematic procedure which bases on a multi-step experimental design approach for determining the efficient system parameters for AIS is presented. Experimental results show that, the artificial immune system algorithm is more efficient than both the classical heuristic flow shop scheduling algorithms and simulated annealing.

Anahtar Kelimeler


Flow Shop Scheduling; Artificial Immune Systems; Clonal Selection

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Creative Commons Lisansı
Doğuş Üniversitesi Dergisi'nin içeriği Creative Commons Atıf-Gayriticari 4.0 Uluslararası Lisansı ile lisanslanmıştır.
 

İletişim:

Doğuş Üniversitesi Dergisi
Acıbadem Zeamet Sokak, No: 21
34722 - Kadıköy, İSTANBUL
E-posta: journal@dogus.edu.tr