Abstract
In the real industrial scenario, the setup times and delivery times are two non-negligible factors, but only few studies have considered the open shop scheduling problem with sequence-dependent setup times and delivery times (OSSP-STDT). In this paper, a mixed integer linear programming model is formulated firstly to accurately solve small-size problems, but it will fail when the size of the problem increases. Then, a complex scheduling network model is developed to characterize OSSP-STDT. After comprehensively considering the local topological features and time attributes in the complex network model, an effective heuristic rule based on complex network is established for solving large-size problems. Finally, an actual warehouse scheduling problem is converted into the aforementioned problem and used as one typical application scenario. Experiments have been conducted and computational results show that compared with exact solutions and meta-heuristics, the proposed algorithm can solve the large-size open shop scheduling problem with sequence-dependent setup times and delivery times more effectively and efficiently.
Highlights
Scheduling is a decision-making process that plays a crucial role in manufacturing and service industry [1]
The open shop scheduling problem with sequence-dependent setup times and delivery times is transformed into reasonably arranging the node traversal order with the goal of traversing all nodes in the network as quickly as possible, on condition that each node and edge has a traversal time, and only the disconnected nodes can be traversed simultaneously
Considering that both the local topological characteristics and time attributes in complex network model can provide heuristic information, an efficient fast traversal greedy algorithm is developed
Summary
Scheduling is a decision-making process that plays a crucial role in manufacturing and service industry [1]. During the latest scientific and technological revolution, the research and application of scheduling algorithms were mainly oriented to the processing of jobs. The core idea was to optimize the processing procedures through scheduling algorithms in order to improve the level of informatization and automation in the workshop; thereby driving production. The strong rise of smart manufacturing [2]–[4] has expanded the simple job-oriented scheduling problem to the scheduling problem for an entire shop resource pool. Along with the wave of development of smart manufacturing, the demand for production and logistics scheduling by typical manufacturing companies has gradually changed from resource transparency, The associate editor coordinating the review of this manuscript and approving it for publication was Kuo-Ching Ying
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