Scheduling
Bahareh Vaisi; Hiwa Farughi; Sadigh Raissi; Heibatolah Sadeghi
Abstract
In this study, we model a stochastic scheduling problem for a robotic cell with two unreliable machines susceptible to breakdowns and subject to the probability of machine failure and machine repair. A single gripper robot facilitates the loading/unloading of parts and cell-internal movement. Since it ...
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In this study, we model a stochastic scheduling problem for a robotic cell with two unreliable machines susceptible to breakdowns and subject to the probability of machine failure and machine repair. A single gripper robot facilitates the loading/unloading of parts and cell-internal movement. Since it is more complicated than the other cycles, the focus has been on the S_2 cycle as the most frequently employed robot movement cycle. Therefore, a multi-objective mathematical formulation is proposed to minimize cycle time and operational costs. The -constraint method is used to solve small-sized problems. Non-dominated sorting genetic algorithm II (NSGA-II), is used to solve large-sized instances based on a set of randomly generated test problems. The results of several Test problems were compared with those of the GAMS software to evaluate the algorithm's performance. The computational results indicate that the proposed algorithm performs well. Compared to GAMS software, the average results for maximum spread (D) and non-dominated solutions (NDS) are 0.02 and 0.04, respectively.
Alborz Hajikhani; Mahtab Panahifard; Mohsen Malekmohamadi; Azar Azadi; Jamshid Bahrami
Volume 1, Issue 4 , October 2014, , Pages 250-258
Abstract
In this paper, the problem of scheduling in a two-stage supply chain system is investigated with considering coordinated scheduling of different stages. The objective is to find the similar sequences of processing tasks in two steps with two aims of minimizing the total preparation time as well as the ...
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In this paper, the problem of scheduling in a two-stage supply chain system is investigated with considering coordinated scheduling of different stages. The objective is to find the similar sequences of processing tasks in two steps with two aims of minimizing the total preparation time as well as the maximum preparation time of each stage. To do so, the problem has been solved by non-dominant sorting genetic algorithm (NSGA-II) and using a variety of multi-objective techniques. The proposed meta-heuristic algorithm is applied for the first time in this problem. The results show that the proposed algorithm is able to find Pareto optimal solutions with a high efficiency.
