Steel production optimization scheduling method based on greedy strategy
A technology for optimizing scheduling and greedy strategy, applied in biological models, instruments, computing models, etc., can solve problems such as different workpiece process routes, multiple idle periods of production lines, and impact on enterprise production efficiency.
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Embodiment 1
[0044] A method for optimal scheduling of steel production based on a greedy strategy, comprising the following steps:
[0045] S1: Obtain the total production task from the production purchase and sales contract, and then decompose each production task into several production sub-tasks according to the production process;
[0046] S2: According to the relevant information of the workshop production line, generate a production line information table, and each production line completes a process;
[0047] S3: Create a structure array T and a process information array W, the structure array T is a set of decomposed production subtasks, the process information array W stores process information, and sequentially associate the production subtasks with the corresponding production subtasks according to the processing sequence Establish connection with the process information to find the predecessor of the production subtask;
[0048] S4: Using the greedy algorithm, the production ...
Embodiment 2
[0052] This embodiment is on the basis of embodiment 1:
[0053] The antecedent is the object to be processed of the production subtask, and the process information corresponding to the first subtask of the production task is no antecedent.
[0054] The information stored in the production line information table includes the procedures, task sequences and processing time records corresponding to each production line.
[0055] In the S3 step, the information stored in the structure array T includes the corresponding production line, processing time, front parts and delivery date; the information stored in the process information array W includes the processing status of the production subtask and the completed processing time.
Embodiment 3
[0057] This embodiment is on the basis of embodiment 1:
[0058] Described greedy algorithm comprises the following steps:
[0059] S41: sort all production subtasks of the total production task in order of delivery date, if the delivery date is the same, sort in descending order of processing time;
[0060] If there are 2 production tasks and each production task has 3 production subtasks, then:
[0061] The production subtasks 1, 2, and 3 of task 1 are filled in T[1], T[2], and T[3] respectively, and the corresponding process information is: W[1], W[2], W[3] ].
[0062] The production subtasks 1, 2, and 3 of task 2 are respectively filled in T[4], T[5], and T[6], and the corresponding process information is: W[4], W[5], and W[6] ].
[0063] First sort by delivery date, the subtasks of task 1 must be arranged together, and then sort each subtask in descending order of processing time to extract the current subtask.
[0064] S42: Collect the sorted production subtasks seq...
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