Abstract
In this paper, a job shop scheduling problem with material handling (JSSMH) is analysed given variable job processing time. The material handling is conducted by automatic guided vehicles (AGVs). Optimisation models have been formulated to accommodate the processing time variability due to random effects and deterioration. With random processing time, the model is formulated as a stochastic programming-based JSSMH (SP-JSSMH) model, and with deteriorating processing time the model can be nonlinear under specific deteriorating functions. A case study was conducted to illustrate and validate the model. The SP-JSSMH models were solved with Pyomo and deteriorating JSSMH models were linearised and solved with CPLEX. By considering variable processing time, the JSSMH models can better adapt to real production scenarios.
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