• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.121-135
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• 2007

Constraint directed scheduling techniques, representing problem constraints explicitly and constructing schedules by constrained heuristic search, have been successfully applied to real world scheduling problems that require satisfying a wide variety of constraints. However, there has been little basic research on the representation and optimization of the objective value of a schedule in the constraint directed scheduling literature. In particular, the cost objective is very crucial for enterprise decision making to analyze the effects of alternative business plans not only from operational shop floor scheduling but also through strategic resource planning. This paper aims to explicitly represent and optimize the total cost of a schedule including the tardiness and inventory costs while satisfying non-relaxable constraints such as resource capacity and temporal constraints. Within the cost based scheduling framework, a cost propagation algorithm is presented to update cost information throughout temporal constraints within the same job.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.237-242
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• 2002

The sales activity of most of small manufacturing companies is based on orders of buyers. The process of promotion, receipt and selection of orders of the manufacturers is closely coupled with the load status of the production lines. The decision on whether to accept an order or not, or the selection of optimal order set among excessive orders is entirely dependent on the schedule of production lines. However, in the real world, since the production scheduling activity is mainly performed by human experts, most of small manufacturers are suffer from being unable to meet due dates, lack of rapid decision on the acceptance of new order. To cope with this problem, this paper deals with the development of an agent for selecting an optimal order set automatically. The main engine of selection agent is based on the typical job-shop scheduling model since our target domain is the injection molding company. To solve the problem, we have formulated it as IP (Integer Program) model, and it has been successfully implemented by ILOG and selection agent. And we have suggested an architecture of an agent for tackling web based order selection problems.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.1
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• pp.41-41
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• 1992

In the real world situations that some jobs need be processed only on certain limited machines frequently occur due to the capacity restrictions of machines such as tools fixtures or material handling equipment. In this paper we consider n-job non-preemptive and m parallel machines scheduling problem having two machines group. The objective function is to minimize the sum of earliness and tardiness with different release times and due dates. The problem is formulated as a mixed integer programming problem. The problem is proved to be Np-complete. Thus a heuristic is developed to solve this problem. To illustrate its suitability and efficiency a proposed heuristic is compared with a genetic algorithm and tabu search for a large number of randomly generated test problems in ship engine assembly shop. Through the experimental results it is showed that the proposed algorithm yields good solutions efficiently.