PENYELESAIAN MULTI-OBJECTIVE FLEXIBLE JOB SHOP SCHEDULING PROBLEM MENGGUNAKAN HYBRID ALGORITMA IMUN

https://doi.org/10.22146/teknosains.22901

Yabunayya Habibi(1*), Galandaru Swalaganata(2), Aprilia Divi Yustita(3)

(1) Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Sepuluh Nopember
(2) Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Sepuluh Nopember
(3) Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Sepuluh Nopember
(*) Corresponding Author

Abstract


Flexible Job shop scheduling problem (FJSSP) is one of scheduling problems with specification: there is a job to be done in a certain order, each job contains a number of operations and each operation is processed on a machine of some available machine. The purpose of this paper is to solve Multi-objective Flexible Job Shop scheduling problem with minimizing the makespan, the biggest workload and the total workload of all machines. Because of complexity these problem, a integrated approach Immune Algorithm (IA) and Simulated Annealing (SA) algorithm are combined to solve the multi-objective FJSSP. A clonal selection is a strategy for generating new antibody based on selecting the antibody for reproduction. SA is used as a local search search algorithm for enhancing the local ability with certain probability to avoid becoming trapped in a local optimum. The simulation result have proved that this hybrid immune algorithm is an efficient and effective approach to solve the multi-objective FJSSP


Keywords


Flexible Job Shop Scheduling; Immune Algorithm; Multi-objective optimization; Simulated Annealing

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DOI: https://doi.org/10.22146/teknosains.22901

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Copyright (c) 2017 Yabunayya Habibi, Galandaru Swalaganata, Aprilia Divi Yustita

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