A research survey: review of flexible job shop scheduling techniques

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An effective heuristic for flexible job-shop scheduling problem with maintenance activities

Abstract We present a simulation-based real-time scheduling methodology for a flexible manufacturing system. Developed is a scheduling mechanism in which the job dispatching rule varies dynamically based on information from discrete event simulation that evaluates a set of candidate rules. Major components of the scheduling mechanism are a simulation mechanism and a real-time control system. The simulation mechanism evaluates dispatching rules and selects the best dispatching rule for a given criterion. The real-time control system periodically monitors the shop floor and checks the performance value of the system. The selected dispatching rule is used until the difference between the actual performance value and the value estimated by simulation exceeds a given limit. Then a new simulation is performed with the remaining operations in the simulation mechanism to select a new rule. Results of computational tests show that the scheduling mechanism can be used effectively in real situations because it can fully use the information on the actual state of shop floors.

Simulation-based real-time scheduling in a flexible manufacturing system = 유연생산 시스템에서 시뮬레이션에 기초한 실시간 일정계획에 관한 연구

Considering the fuzzy nature of the data in real-world scheduling, an effective estimation of distribution algorithm (EDA) is proposed to solve the flexible job-shop scheduling problem with fuzzy processing time. A probability model is presented to describe the probability distribution of the solution space. A mechanism is provided to update the probability model with the elite individuals. By sampling the probability model, new individuals can be generated among the search region with promising solutions. Moreover, a left-shift scheme is employed for improving schedule solution when idle time exists on the machine. In addition, some fuzzy number operations are used to calculate scheduling objective value. The influence of parameter setting is investigated based on the Taguchi method of design of experiment, and a suitable parameter setting is suggested. Numerical testing results and comparisons with some existing algorithms are provided, which demonstrate the effectiveness of the proposed EDA.

An effective estimation of distribution algorithm for the flexible job-shop scheduling problem with fuzzy processing time

Flexible job shop scheduling problem (FJSP) is an NP-hard combinatorial optimisation problem, which has significant applications in the real world. Due to its complexity and significance, lots of attentions have been paid to tackle this problem. In this study, the existing solution methods for the FJSP in recent literature are classified into exact algorithms, heuristics and meta-heuristics, which are reviewed comprehensively. Moreover, the real-world applications of the FJSP are also introduced. Finally, the development trends of the manufacturing industry are analysed, and the future research opportunities of the FJSP are summarised in detail.

Review on flexible job shop scheduling

Scheduling for the flexible job-shop is a very important issue in both fields of combinatorial optimization and production operations. However, due to combination of the routing and sequencing problems, flexible job-shop scheduling problem (FJSP) presents additional difficulty than the classical job-shop scheduling problem and requires more effective algorithms. This paper developed a filtered-beam-search-based heuristic algorithm (named as HFBS) to find sub-optimal schedules within a reasonable computational time for the FJSP with multiple objectives of minimising makespan, the total workload of machines and the workload of the most loaded machine. The proposed algorithm incorporates dispatching rules based heuristics and explores intelligently the search space to avoid useless paths, which makes it possible to improve the search speed. Through computational experiments, the performance of the presented algorithm is evaluated and compared with those of existing literature and those of commonly used dispa...

A filtered-beam-search-based heuristic algorithm for flexible job-shop scheduling problem

In the practical production process of a flexible manufacturing system (FMS), unexpected disturbances such as rush orders arrival and machine breakdown may inevitably render the existing schedule infeasible. This makes dynamic rescheduling necessary to respond to the disturbances and to improve the efficiency of the disturbed FMS. Compared with the static scheduling, the dynamic rescheduling relies on more effective and robust search approaches for its critical requirement of real-time optimal response. In this paper, a filtered-beam-search (FBS) -based heuristic algorithm is proposed to solve the dynamic rescheduling problem in a large and complicated job shop FMS environment with realistic disturbances. To enhance its performance, the proposed algorithm makes improvement in the local/global evaluation functions and the generation procedure of branches. With respect to a due date-based objective (weighted quadratic tardiness), computational experiments are studied to evaluate the performance of the proposed algorithm in comparison with those of other popular methods. The results show that the proposed FBS-based algorithm performs very well for dynamic rescheduling in terms of computational efficiency and solution quality.

Filtered-beam-search-based algorithm for dynamic rescheduling in FMS

In this paper, an agent-based Decision Support System (DSS) for the effective dynamic scheduling of a Flexible Manufacturing System (FMS) is proposed. The proposed DSS mainly includes six components: User Interface Agent (UIA), Criteria And Rules Selection Agent (CRSA), Performance Evaluation Agent (PEA), Scheduling Decision Selection Agent (SDSA), FMS database and Scheduling Knowledge Base (SKB). Functions of each component are discussed and a corresponding prototype system is developed. Finally, some examples are used to illustrate the decision process and to study the performance of the FMS under different dynamic disturbances.

Agent-based decision support system for dynamic scheduling of a flexible manufacturing system

A modeling method of extended knowledge hybrid Petri nets (EKHPNs), incorporating object-oriented methods into hybrid Petri nets (HPNs), was presented and used for the representation and modeling of semiconductor wafer fabrication flows To model the discrete and continuous parts of a complex semiconductor wafer fabrication flow, the HPNs were introduced into the EKHPNs Object-oriented methods were combined into the EKHPNs for coping with the complexity of the fabrication flow Knowledge annotations were introduced to solve input and output conflicts of the EKHPNs Finally, to demonstrate the validity of the EKHPN method, a real semiconductor wafer fabrication case was used to illustrate the modeling procedure The modeling results indicate that the proposed method can be used to model a complex semiconductor wafer fabrication flow expediently

Wang Shi-jin

Papers

A filtered-beam-search-based heuristic algorithm for flexible job-shop scheduling problem

Filtered-beam-search-based algorithm for dynamic rescheduling in FMS

Agent-based decision support system for dynamic scheduling of a flexible manufacturing system

A modeling method of semiconductor fabrication flows with extended knowledge hybrid Petri nets