• Korean Management Science Review
• /
• v.20 no.1
• /
• pp.51-64
• /
• 2003

The JSSP (Job Shop Scheduling Problem) Is one of the most general and difficult of all traditional scheduling problems. The goal of this research is to develop an efficient scheduling method based on genetic algorithm to address JSSP. we design scheduling method based on SGA (Single Genetic Algorithm) and PGA (Parallel Genetic Algorithm). In the scheduling method, the representation, which encodes the job number, is made to be always feasible, initial population is generated through integrating representation and G&T algorithm, the new genetic operators and selection method are designed to better transmit the temporal relationships in the chromosome, and island model PGA are proposed. The scheduling method based on genetic algorithm are tested on five standard benchmark JSSPs. The results were compared with other proposed approaches. Compared to traditional genetic algorithm, the proposed approach yields significant improvement at a solution. The superior results indicate the successful Incorporation of generating method of initial population into the genetic operators.

• Industrial Engineering and Management Systems
• /
• v.6 no.2
• /
• pp.119-124
• /
• 2007

The most difficult and time-intensive issue in the successful implementation of genetic algorithms is to find good parameter setting, one of the most popular subjects of current research in genetic algorithms. In this study, we present a new efficient experimental design method for parameter optimization in a genetic algorithm for general job shop scheduling problem using the Taguchi method. Four genetic parameters including the population size, the crossover rate, the mutation rate, and the stopping condition are treated as design factors. For the performance characteristic, makespan is adopted. The number of jobs, the number of operations required to be processed in each job, and the number of machines are considered as noise factors in generating various job shop environments. A robust design experiment with inner and outer orthogonal arrays is conducted by computer simulation, and the optimal parameter setting is presented which consists of a combination of the level of each design factor. The validity of the optimal parameter setting is investigated by comparing its SN ratios with those obtained by an experiment with full factorial designs.

• Industrial Engineering and Management Systems
• /
• v.7 no.2
• /
• pp.84-92
• /
• 2008

Scheduling is one of the most important issues in the planning and operation of production systems. This paper investigates a general job shop scheduling problem with reentrant work flows and sequence dependent setup times. The disjunctive graph representation is used to capture the interactions between machines in job shop. Based on this representation, four two-phase heuristic procedures are proposed to obtain near optimal solutions for this problem. The obtained solutions in the first phase are substantially improved by reversing the direction of some critical disjunctive arcs of the graph in the second phase. A comparative study is conducted to examine the performance of these proposed algorithms.

• Journal of Korean Society for Quality Management
• /
• v.16 no.1
• /
• pp.32-42
• /
• 1988

The general n/m job-shop problem is easy to state what is required, but it is extremely difficult to make any progress whatever toward a solution. This paper was first to examine a heuristic procedure of general n/m scheduling generation focused on the procedure of MWRK (Most Work Remaining) presented by Giffler and Thompson (1960) among others. Then modified procedure was proposed to obtain better solution in light of the key measure of performance compared with that of the literature presented by Baker (1974). The modified procedure then has been extended to other example problem to test the better results and to assure the properness of application.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.348-352
• /
• 2000

Intelligent agents represent parts and manufacturing resources, which cooperate, negotiate, and compete with each other. The negotiation between agents is in general based on the Contract-Net-Protocol. This paper describes a new approach to negotiation-based job shop scheduling. The proposed method includes multi-negotiation strategy as well as single-negotiation. A case study showing the comparison of various negotiation strategies is also given.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.23 no.59
• /
• pp.11-20
• /
• 2000

The Job Shop Scheduling Problem(JSSP) is one of the most general and difficult of all traditional scheduling problems. The goal of this research is to develop an efficient scheduling method based on single genetic algorithm(SGA) and parallel genetic algorithm (PGA) to address JSSP. In this scheduling method, new genetic operator, generating method of initial population are developed and island model PGA are proposed. The scheduling method based on PGA are tested on standard benchmark JSSP. The results were compared with SGA and another GA-based scheduling method. The PGA search the better solution or improves average of solution in benchmark JSSP. Compared to traditional GA, the proposed approach yields significant improvement at a solution.

• Korean Management Science Review
• /
• v.10 no.2
• /
• pp.61-77
• /
• 1993

This paper involves a study of developing the production scheduling system in a general job shop type mechanical factory. We consider realistic situations in the job-shop environments, such as alternative machines for operation, the new kinds of processes, the machining center with the plural pallet, the operational situation of each machine during the scheduling period, occurings of urgent orders and machine breakdowns. We also propose the methodology of re-schedule. It is very fast and acceptable for real time production control system. These all functions are implemented on IBM PC and program source is written in PASCAL language.

• Korean Management Science Review
• /
• v.10 no.1
• /
• pp.171-192
• /
• 1993

In this paper, a rule for dispatching operations, named the Most Dissimilar Resources (MDR) dispatching rule is presented. The MDR dispatching rule has been designed to maximize utilization of resources in a resource-constrained job shop with general precedence constraints. In shown that solving the above scheduling problem with the MDR dispatching rule is equivalent to multiple solving of the maximum clique problem. A graph theoretic approach is used to model the latter problem. The pairwise counting heuristic of computational time complexity O(n$^{2}$) is developed to solve the maximum clique problem. An attempt is made to combine the MDR dispatching rule with the existing look-ahead dispatching rules. Computational experience indicates that the combined MDR dispatching rules provide solutions of better quality and consistency than the dispatching rules tested in a resource-constrained job shop.

• Management Science and Financial Engineering
• /
• v.9 no.2
• /
• pp.47-68
• /
• 2003

We consider the customer order scheduling problem with job capacity restriction where the number of jobs in the shop at the same time is fixed. In the customer order scheduling problem, each job is part of some batch (customer order) and the composition of the jobs (product) in the batch is pre-specified. The objective function is associated with the completion time of the batches instead of the completion time of the jobs. We first summarize the known results for the general customer order scheduling problems. Then, we establish some new properties for the problems with job capacity restriction. For the case of unit processing time with the objective of minimizing makespan, we develop a polynomial-time optimal procedure for the two machine case. For the same problem with a variation of no batch alternation, we also develop a polynomial-time optimal procedure. Then, we show that the problems with the objectives of minimizing makespan and minimizing average batch completion time become NP-hard when there exist arbitrary number of machines. Finally, We propose optimal solution procedures for some special cases.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2004.05a
• /
• pp.64-66
• /
• 2004

In general, the algorithms for production scheduling are developed with special objective under the special restrictions. Therefore, there is no common algorithm for APS system applied to various kind of production circumstances. The scheduling algorithm for APS system has to solve any problem that comes from any conditions of product kind, process, resource, machine, special rule for scheduling, and so forth. In addition, the algorithm finds solutions quickly because the need for real time based reschedule comes out often. In this paper, I am going to develop a scheduling algorithm using heuristic and genetic algorithm for APS system applied to various kind of production circumstances quickly and flexibly. The developed APS system with the algorithm will be introduced in this paper, also.