“…A distinctive feature of this algorithm in comparison with the similar algorithm given in Mauergauz Y. [17] is the presence of step 8 to determine the contents of buffers. The corresponding procedure is carried out according to rules a)-e) of the previous paragraph.…”
This paper contains the example of sectoral APS systems, for which the problem algorithmic space coincides with the relevant operational environment with great accuracy. The method of scheduling for technological processes with looping is described, based on the simultaneous application of two criteria: the value of relative direct costs and the average utility of order fulfillment. The influence of buffers on the work of shops is considered. The proposed method provides an automatic grouping of the same type of jobs on all machines involved while taking into account the required duration of jobs. A package of application programs has been developed that allows planning for an average number of orders. The result of the program is a set of non-dominant (not improved) options that are offered to the user for making a final decision.
“…A distinctive feature of this algorithm in comparison with the similar algorithm given in Mauergauz Y. [17] is the presence of step 8 to determine the contents of buffers. The corresponding procedure is carried out according to rules a)-e) of the previous paragraph.…”
This paper contains the example of sectoral APS systems, for which the problem algorithmic space coincides with the relevant operational environment with great accuracy. The method of scheduling for technological processes with looping is described, based on the simultaneous application of two criteria: the value of relative direct costs and the average utility of order fulfillment. The influence of buffers on the work of shops is considered. The proposed method provides an automatic grouping of the same type of jobs on all machines involved while taking into account the required duration of jobs. A package of application programs has been developed that allows planning for an average number of orders. The result of the program is a set of non-dominant (not improved) options that are offered to the user for making a final decision.
“…The manufacturer's attitude to the order changes with time, and the appropriate function is named production intensity. This function for multistage manufacturing and order execution without preemption (in a single batch) is [19] as…”
Section: Main Problem Definitions and Utility Functionsmentioning
confidence: 99%
“…Thus, the operation finishes at the moment t k + p kj . As it was demonstrated in [19], the utility of the entire set of orders at any level of operation tree may be computed by one of two recurrent formulas, which are used, if the utility value is known at the previous level: integrals and necessary tables are described in [20].…”
Section: Page 16mentioning
confidence: 99%
“…The Pareto compromise curve serves as such limit, because in its points the criterion U improvement (diminution) means the criterion V deterioration (diminution). For solving the problem (10), similar to [19], it makes sense to apply the method, based on the MO-Greedy approach [21].…”
Section: Fig 1 Example Of Flexible Multiproduct Batch Linementioning
This paper presents a method for multistage multiproduct batch scheduling based on two criteria simultaneously: relative setup cost criterion and average orders utility criterion. Batch size is determined at the first operation and will not change further. During scheduling process batches are automatically grouped by product types for cost decreasing. Storing between operations is unavailable. In this method, the concept of production intensity as a dynamic production process parameter is used. A software package allows scheduling for medium quantity of jobs. The result of software application is the set of non-dominant versions proposed to a user for making a final choice.
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