Date of Award


Publication Type

Master Thesis

Degree Name



Industrial and Manufacturing Systems Engineering

First Advisor

ElMaraghy, Hoda (Industrial and Manufacturing Systems Engineering)


Operations research.




The flexible job shop scheduling problem (F-JSSP) is mathematically formulated. One novel position-based and three sequence-based mixed integer linear programming models are developed. Since F-JSSPs are strongly NP-hard, MILPs fail to solve large-size instances within a reasonable timeframe. Thus, a meta-heuristic, a hybrid of artificial immune and simulated annealing (AISA), is developed for use with larger instances of the F-JSSP. To prove the efficiency of developed MILPs and AISA, they are compared against state-of-the-art MILPs and meta-heuristics in literature. Comparative evaluations are conducted to test the quality and performance of the developed models and solution technique respectively. To this end, size complexities of the developed MILPs are investigated. The acquired results demonstrate that the proposed MILPs outperform the state-of-the-art MILP models in literature. Likewise, the proposed AISA outperforms all the previously developed meta-heuristics. The developed AISA has successfully been applied to a realistic case study from mould and die industry.