Abstract
A simulated annealing approach based simulation-optimisation to the dynamic job-shop scheduling problem
Highlights
Scheduling is to allocate the production resources to the activities that must be done [1]
The schedule provided for a dynamic job-shop scheduling problem (DJSP) should possess sufficient qualifications to tackle with machine failures and changing due dates
Three scheduling rules (SRs), i.e. earliest due date rule (EDD), shortest processing time first rule (SPT) and first in first out rule (FIFO), are incorporated into simulation model (SM) accounting for the machine failures
Summary
Scheduling is to allocate the production resources (e.g., man-power, machine and time) to the activities that must be done [1]. The activities are subject to the precedence relationships because of technological constraints of the allocated resources [2] and to be specified in a sequential order [3]. Scheduling effects the performance of production systems [4]. A good scheduling reduces the effort, time or cost of the production [5],[6]. The shop scheduling problems are categorized in several production types such as job-shop, flow-shop, open-shop, mixed-shop and group-shop [7]. In a job-shop scheduling problem (JSP), the jobs are sequenced in an order that the operations are performed in multiple machine [8]. JSP is a common problem in most of production environment [9]
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