• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.22 no.52
• /
• pp.297-309
• /
• 1999

Resource Constrained Dynamic Multi-Projects Scheduling(RCDMPS) is intended to minimize the total processing time(makespan) of two or more projects sequentially arriving at the shop under restricted resources. The aim of this paper is to develop the new Tabu Search heuristic for RCDMPS to minimize makespan. We propose the insertion method to generate the neighborhood solutions in applying the Tabu Search for the RCDMPS and the diversification strategy to search the solution space diversely. The proposed diversification strategy apply the dynamic tabu list that the tabu list size is generated and renewed at each iteration by the complexity of the project, and change the proposed tabu attribute. In this paper, We use the dynamic tabu list for the diversification strategy and intensification strategy in the tabu search, and compare with other dispatching heuristic method to verify that the new heuristic method minimize the makespan of the problem.

• Journal of Convergence for Information Technology
• /
• v.9 no.12
• /
• pp.124-132
• /
• 2019

Scheduling problems can be classified into offline and online ones. This paper considers an online scheduling problem to minimize makespan on the identical parallel machines. For dynamically arrived jobs with their ready times, we show that the sequencing order according to the ERD (Earliest Ready Date) rule is optimal to minimize makespan. This paper suggests an algorithm by using the MIP(Mixed Integer Programming) formulation periodically to find a good periodic schedule and evaluates the required computational time and resulted makespan of the algorithm. The comparition with an offline scheduling shows our algorithm makes the schedule very fast and the makespan can be reduced as the period time reduction, so we can conclude that our algorithm is useful for scheduling the jobs under online environment even though the number of jobs and machines is large. We expect that the algorithm is invaluable one to find good schedules for the smart factory and online scheduler using the blockchain mechanism.

• Journal of the Korea Safety Management & Science
• /
• v.25 no.2
• /
• pp.1-8
• /
• 2023

This paper is proposing a novel machine scheduling model for the unrelated parallel machine scheduling problem without setup times to minimize the total completion time, also known as "makespan". This problem is a NP-complete problem, and to date, most approaches for real-life situations are based on the operator's experience or simple heuristics. The new model based on the Memetic Algorithm, which was proposed by P. Moscato in 1989, is a hybrid algorithm that includes genetic algorithm and local search optimization. The new model is tested on randomly generated datasets, and is compared to optimal solution, and four scheduling models; three rule-based heuristic algorithms, and a genetic algorithm based scheduling model from literature; the test results show that the new model performed better than scheduling models from literature.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.30 no.2
• /
• pp.44-50
• /
• 2007

This paper deals with the problem of scheduling jobs and rate-modifying activities on parallel machines. A rate-modifying activity is an activity that changes the production rate of equipment such as maintenance and readjustment. If a job is scheduled after the rate-modifying activity, then the processing time varies depending on the modifying rate of the activity. In this study, we extend the single machine problem to parallel machines problem and propose algorithms is to schedule the rate-modifying activities and jobs to minimize the makespan on parallel machines which is NP-hard. We propose a branch and bound algorithm with three lower bounds to solve medium size problems optimally. Also we develop three heuristics, Modified Longest Processing Time, Modified MULTIFIT and Modified COMBINE algorithms to solve large size problems. The test results show that branch and bound algorithm finds the optimal solution in a reasonable time for medium size problems (up to 15 jobs and 5 machines). For large size problem, Modified COMBINE and Modified MULTIFIT algorithms outperform Modified LPT algorithm in terms of solution quality.

• Korean Management Science Review
• /
• v.30 no.3
• /
• pp.81-97
• /
• 2013

This paper considers a parallel-machine scheduling problem with dedicated and common processing machines. Non-identical setup and processing times are assumed for each machine. A genetic algorithm is proposed to minimize the makespan objective measure. In this paper, a lowerbound and some heuristic algorithms are derived and tested through computational experiments.

• Journal of Korean Institute of Industrial Engineers
• /
• v.12 no.1
• /
• pp.1-11
• /
• 1986

This research is concerned with n jobs, m parallel identical machines scheduling problem in which all jobs have a common due date. The objective of the research is to develop an optimum scheduling algorithm for determining an optimal job sequence, the optimal value of the common due date and the minimum makespan to minimize total cost. The total cost is based on the common due date cost, the earliness cost, the tardiness cost and the flow time cost of each job in the selected sequence. The optimum scheduling algorithm is developed. A numerical example is given to illustrate the scheduling algorithm.

• Korean Management Science Review
• /
• v.12 no.2
• /
• pp.77-87
• /
• 1995

In this paper we develop an efficient heuristic algorithm for the problem of scheduling n sequence-dependent jobs on a basic processor to minimize makespan. Efficient solution methods are already known for the sequence- independent case. But for the sequence-dependent case, this problem belongs to a set of strong NP-complete problems. We present a heuristic which is similar to shortest setup time heuristic but opportunity cost of setup time rather than shortest setup time is used for choosing next job. This heuristic algorithm has same computational complexity and worst case ratio as the shortest setup time heuristic. We used Wilcoxon signed rank test to show that our heuristic is superior to nearest setup time heuristic in term of average behavior.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.16 no.2
• /
• pp.14-35
• /
• 1991

The purpose of this study is to develop an efficient exact algorithm for the problem of scheduling n in dependent jobs on m unequal parallel processors to minimize makespan. Efficient solutions are already known for the preemptive case. But for the non-preemptive case, this problem belongs to a set of strong NP-complete problems. Hence, it is unlikely that the polynomial time algorithm can be found. This is the reason why most investigations have bben directed toward the fast approximate algorithms and the worst-case analysis of algorithms. Recently, great advances have been made in mathematical theories regarding Lagrangean relaxation and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining these mathematical tools with branch-and-bound procedures, these have been some successes in constructing pseudo-polynomial time algorithms for solving previously unsolved NP-complete problems. This study applied similar methodologies to the unequal parallel processor problem to find the efficient exact algorithm.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.16 no.2
• /
• pp.13-35
• /
• 1991

The purpose of this study is to develop an efficient exact algorithm for the problem of scheduling n in dependent jobs on m unequal parallel processors to minimize makespan. Efficient solutions are already known for the preemptive case. But for the non-preemptive case, this problem belongs to a set of strong NP-complete problems. Hence, it is unlikely that the polynomial time algorithm can be found. This is the reason why most investigations have bben directed toward the fast approximate algorithms and the worst-case analysis of algorithms. Recently, great advances have been made in mathematical theories regarding Lagrangean relaxation and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining and the subgradient optimization procedure which updates the Lagrangean multipliers. By combining these mathematical tools with branch-and-bound procedures, these have been some successes in constructing pseudo-polynomial time algorithms for solving previously unsolved NP-complete problems. This study applied similar methodologies to the unequal parallel processor problem to find the efficient exact algorithm.

• Management Science and Financial Engineering
• /
• v.17 no.1
• /
• pp.95-116
• /
• 2011

This paper considers a flowshop scheduling problem where a customer orders multiple products (jobs) from a production facility. The objectives are to minimize makespan and to minimize the sum of order (batch) completion times. The order cannot be shipped unless all the products in the order are manufactured. This problem was motivated by numerous real world problems encountered by a variety of manufacturers. For the makespan objective, we develop an optimal solution procedure which runs in polynomial time. For the sum of order completion time objective, we establish the complexity of the problem including several special cases. Then, we introduce a simple heuristic and find an asymptotically tight worst case bound on relative error. Finally, we conclude the paper with some implications.