• Journal of Convergence for Information Technology
• /
• v.11 no.8
• /
• pp.207-211
• /
• 2021

This paper addresses a two-stage flexible flow shop scheduling problem in which there is one machine in stage 1 and two identical machines in stage 2. The objective is the minimization of the total completion time. The problem is formulated by a mixed integer quadratic programming (MIQP) and a hybrid simulated annealing (HSA) is proposed to solve the MIQP. The HSA adopts the exploration capabilities of a genetic algorithm and incorporates a simulated annealing to reduce the premature convergence. Extensive computational tests on randomly generated problems are carried out to evaluate the performance of the HSA.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2003.05a
• /
• pp.145-150
• /
• 2003

The parallel machine scheduling problem or assigning n jobs on m identical machines with the objective of minimizing makespan is considered. In this note, we apply the PTAS (Polynomial Time Approximation Scheme) or Hochbaum and Shmoys to our problem and show that it is still a PTAS for our problem.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.7
• /
• pp.1702-1710
• /
• 2009

In this paper, we propose a problem space based search(PSBS) algorithm to solve parallel machine scheduling problem considering rework probabilities. For each pair of a machine and a job type, rework probability of each job on a machine can be known through historical data acquisition. Neighborhoods are generated by perturbing four problem data vectors (processing times, due dates, setup times, and rework probabilities) and evaluated through the efficient dispatching heuristic (EDDR). The proposed algorithm is measured by maximum lateness and the number of reworked jobs. We show that the PSBS algorithm is considerably improved from the result obtained by EDDR.

• Journal of the Society of Naval Architects of Korea
• /
• v.60 no.3
• /
• pp.202-211
• /
• 2023

The profile shops in shipyards produce section steels required for block production of ships. Due to the limitations of shipyard's production capacity, a considerable amount of work is already outsourced. In addition, the need to improve the productivity of the profile shops is growing because the production volume is expected to increase due to the recent boom in the shipbuilding industry. In this study, a scheduling optimization was conducted for a parallel welding line of the profile process, with the aim of minimizing tardiness and the number of set-up changes as objective functions to achieve productivity improvements. In particular, this study applied a dynamic scheduling method to determine the job sequence considering variability of processing time. A Markov decision process model was proposed for the job sequence problem, considering the trade-off relationship between two objective functions. Deep reinforcement learning was also used to learn the optimal scheduling policy. The developed algorithm was evaluated by comparing its performance with priority rules (SSPT, ATCS, MDD, COVERT rule) in test scenarios constructed by the sampling data. As a result, the proposed scheduling algorithms outperformed than the priority rules in terms of set-up ratio, tardiness, and makespan.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2000.04a
• /
• pp.277-280
• /
• 2000

다중스레드 병렬기계(multithreaded parallel machine)를 위하여 함수 프로그램을 번역할 때 스레드 분할이란 수행 순서를 번역시간에 알 수 있어 정적 스케줄링이 가능한 프로그램의 부분을 식별하여 스레드로 모으는 작업을 말한다. 조건식에서 연산의 수행 순서는 판단식 -> 참실행식 또는 판단식 -> 거짓실행식이므로 번역시간에는 수행순서를 결정할 수 없다. 따라서 기존의 분할 알고리즘은 조건식의 판단식, 참실행식, 거짓실행식을 기본 블록으로 나누고 각각에 대하여 지역 분할을 적용한다. 이러한 제약은 스레드의 정의를 약간 수정하여 스레드 내에서의 분기를 허용한다면 좀더 좋은 분할을 얻을 수 있다. 스레드내에서의 분기는 병렬성을 감소시키거나 동기화의 횟수를 증가시키거나 또는 교착상태를 발생시키는 등의 스레드 분할의 기본 원칙을 어기지 않으며 오히려 스레드 길이를 증가시키거나 동기화 횟수를 줄이는 장점을 가질 수 있다. 본 논문에서는 조건식의 세 가지 기본 블록을 하나 또는 두 개의 기본 블록으로 병합함으로서 스레드 분할을 향상시키는 방법을 제안한다.

• IE interfaces
• /
• v.15 no.4
• /
• pp.338-348
• /
• 2002

In this paper, we present a restricted tabu search(RTS) algorithm that schedules jobs on identical parallel machines in order to minimize the maximum lateness of jobs. Jobs have release times and due dates. Also, sequence-dependent setup times exist between jobs. The RTS algorithm consists of two main parts. The first part is the MATCS(Modified Apparent Tardiness Cost with Setups) rule that provides an efficient initial schedule for the RTS. The second part is a search heuristic that employs a restricted neighborhood generation scheme with the elimination of non-efficient job moves in finding the best neighborhood schedule. The search heuristic reduces the tabu search effort greatly while obtaining the final schedules of good quality. The experimental results show that the proposed algorithm gives better solutions quickly than the existing heuristic algorithms such as the RHP(Rolling Horizon Procedure) heuristic, the basic tabu search, and simulated annealing.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.39 no.3
• /
• pp.83-91
• /
• 2014

We consider the problem of scheduling identical jobs with sequence-independent setup times on parallel machines. The objective is to minimize total completion times. We present the pseudopolynomial-time algorithm for the case with a fixed number of machines and an efficient approximation algorithm for our problem with identical setup times, which is known to be NP-hard even for the two-machine case.