This article deals with the multi-mode multi-project inverse scheduling problem of the turbine assembly workshop in a Chinese electric power station equipment manufacturing firm considering some unexpected disturbance...
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This article deals with the multi-mode multi-project inverse scheduling problem of the turbine assembly workshop in a Chinese electric power station equipment manufacturing firm considering some unexpected disturbances in the assembly process, such as materials delay, equipment failure and parts rework, etc. The objective is to optimize the assembly cost in inversescheduling under the constraints of due date, worker modes, cranes, etc. A modified integer and categorical particle swarm optimization algorithm combined with Tabu search (MICPSO-TS) is proposed. In the proposed MICPSO-TS, double-vector encoding is presented to show the execution modes of activities and overtime schedule of projects which are optimized by ICPSO and TS respectively. A hybrid heuristic decoding algorithm (HHDA) including project order selection rules, crane scheduling rules, resource reservation mechanism and overtime determination rules is proposed. Eventually, the feasibility and effectiveness of the proposed MICPSO-TS are verified by the experimental test data and a real-world engineering case.
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