Afsahr, Puya and Wang, Hong (2011) Multiobjective Meta-Heuristic Product Scheduling for Multi-Machine Manufacturing Systems. In: 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC), December 12-15, Orlando, FL, USA,.

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Flow line are one of the most commonly encountered layouts in manufacturing industries, where several product types (grades) are manufactured using a sequence of sub-systems or machinery with different tasks. With increasing prices of energy and speci�c customer demands employing effective product scheduling strategies has become essential for manufacturing industries to maintain their business viability. In this paper, a new product scheduling method is proposed for multi-machine, multi-product �ow lines. The objective here is to control the production start time for each grade so that the product delivery time errors are minimised. It is also desired to minimise the overall makespan variability caused by non-Gaussian uncertainties formulated by the entropy of the delivery time errors. Therefore, the proposed product scheduling strategy is a nonlinear multi-objective optimisation problem with non-Gaussian uncertainties. To solve this problem, the nonlinear dynamic �ow line model is converted to a linear dynamic equivalent using a (Max,+) algebraic approach. Then, a Proportional-Integral (PI) scheduling controller is used to control the production start time for each grade. The scheduling controller coef�cients are tuned by a MultiObjective Differential Evolution (MODE) algorithm. Simulation results show the effectiveness of the proposed technique and a comparison is made between MODE, Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO).

Item Type: Conference or Workshop Item (Paper)
Additional Information: cicada
Uncontrolled Keywords: cicada
Subjects: MSC 2010, the AMS's Mathematics Subject Classification > 90 Operations research, mathematical programming
MSC 2010, the AMS's Mathematics Subject Classification > 93 Systems theory; control
Depositing User: Mr Houman Dallali
Date Deposited: 12 Jan 2012
Last Modified: 20 Oct 2017 14:13

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