An intelligent optimal production scheduling approach using constraint-based search and agent-based collaboration (original) (raw)
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An Effective Approach for Real-World Production Planning
Proceedings of the First International Conference on Informatics in Control, Automation and Robotics, 2004
This paper shows an application of constraint logic-based approach to the realistic scheduling problem. Operations scheduling, often influenced by diverse and conflicting constraints, is strongly NP-hard problem of combinatorial optimisation. The problem is complicated further by real scheduling environments, where a variety of constraints in response are critical aspects for the application of a solution. Constraint logic programming technique well armed with the major function of constraint handling and solving mechanisms can be effectively applied to solve real-world scheduling problems. In this study, the scheduling problem addressed, based on a dye house involving jobs associated with the colouring of different fibres, is characterized by various constraints like colour precedence, dye machine allocation and time constraints. The solution procedure used takes into account a number of dye house performance measures which include on-time delivery and resource utilisation. The results indicate that constraint-based scheduling is computationally efficient in schedule generation in that a solution can be found within a few seconds. Furthermore, solutions produced always minimise the mean tardiness and maximise the utilisation of dyeing facilities.
AI Magazine, 1986
the constraint knowledge utilized in actual factory environments. This led to the construction of the Intelligent Scheduling and Information System (ISIS), a series of experimental job shop scheduling systems (Fox, Allen, and Strohm 1982; Smith 1984a, 1984b). ISIS-2 was demonstrated in the context of the Westinghouse Turbine Components Plant (WTCP) in Winston-Salem, North Carolina. More recently, we initiated work on a new system called OPIS , which continues to generalize from the ISIS experience and provide greater system flexibility in approaching various scheduling tasks. We feel we have made significant progress in this work, but there are difficult issues that remain to be addressed. This article attempts to coalesce what we have learned thus far and to reflect on the potential of knowledge-based approaches to this difficult problem. Abstract To be useful in practice, a factory production schedule must reflect the influence of a large and conflicting set of requirements, objectives and preferences. Human schedulers are typically overburdened by the complexity of this task, and conventional computer-based scheduling systems consider only a small fraction of the relevant knowledge. This article describes research aimed at providing a framework in which all relevant scheduling knowledge can be given consideration during schedule generation and revision. Factory scheduling is cast as a complex constraint-directed activity, driven by a rich symbolic model of the factory environment in which various influencing factors are formalized as constraints. A variety of constraint-directed inference techniques are defined with respect to this model to provide a basis for intelligently compromising among conflicting concerns. Two Bnowledge-based factory scheduling systems that implement aspects of this approach are described.
Agent-based dynamic scheduling model for product-driven production
Brazilian journal of operations & production management, 2020
Goal: This research provides specific solution for dynamic scheduling of product-driven production with unique level of detail and original architecture. Design / Methodology / Approach: Design process of scheduling problem-solving MAS is divided into three steps: agent encapsulation of entities participating in scheduling, including concept of agents and responsibilities they assume, system architecture and topology of the agents network, detailed design of decision scheme of individual agents. Results: Production processes take place in dynamic environment and have to react to numerous real-time events, hence reschedule the production by a new design and implement agent-based model in order to solve dynamic flexible job shop scheduling problem in product-driven production environment. Limitations of the investigation: Designed model counts with simple agents behaving on conditionaction rules. These agents could be replaced by more sophisticated types of agents such as utilitybased...
Production and Machine Scheduling System Integrated with Materials Requirement Planning
Isico 2013, 2013
Production and machine scheduling is important for any corporation in order to meet the customers demand. Literatures show that integration between customer orders and materials availability is important combination. This paper presents the prototype for a production and machine scheduling system to improve and maximize the integration with materials requirement planning. In this paper, a software development life cycle was applied as the research methodology. The authors used unified modeling language for the analysis and design of the application. After requirements identification phase, the application prototype was built and presented to the application users. The results of this research are an application prototype that helps to record production data and could be accessed to know the production process integrated with materials requirement planning.
In the operation management environment, the process of production scheduling is responsible for detailing operating activities by indicating a set of methods and tools that are conditioned, among other restrictions, by the tactical decisions that are made in the production planning environment. Although, theoretically, a bi-directional flow of information should exist among both environments of decisions that permit those who are involved to coordinate both levels in practice, such does not occur because of a structured decision-making tool gap. This document proposes an architecture that is based on agents software designed with INGENIAS methodology and proposed from an analysis of requirements that is based on CIMOSA. Once it is implemented, a prototype that employs JADE has been carried out to test and verify its suitable operation.
A Mathematical Model for Production Planning and Scheduling in a Production System: A Case Study
2019
Integration in decision making at different organizational and time levels has important implications for increasing the profitability of organizations. Among the important issues of medium-term decision-making in factories, are production planning problems that seek to determine the quantities of products produced in the medium term and the allocation of corporate resources. Furthermore, at short-term, jobs scheduling and timely delivery of orders is one of the vital decision-making issues in each workshop. In this paper, the production planning and scheduling problem in a factory in the north of Iran is considered as a case study. The factory produces cans and bins in different types with ten production lines. Therefore, a mixed integer linear programming (MILP) model is presented for the integrated production planning and scheduling problem to maximize profit. The proposed model is implemented in the GAMS software with the collected data from the real environment, and the optimal...
Mathematical Modeling of Production Scheduling Problem: A Case Study for Manufacturing Industry
International Journal of Science Technology & Engineering
Mathematical formulations for production scheduling environment are very complex task. These complex real life problems cannot be solved by traditional exact solvers to get good quality solutions within feasible time. Inspired by a real-world case study in the manufacturing industry, this paper provides an efficient mathematical model for short-term production scheduling. This model can be easily modified for flexibility and dynamic nature of manufacturing industries. This mathematical model can be optimized by modern optimization methods.
A Knowledge Based Approach to Production Planning and Scheduling in a Metallurgical Company
Decision-making supported by task-oriented software tools plays more and more role in the production companies, including metallurgical plants. Decision-making in production planning and scheduling requires the response in an interactive real-time mode. It is an incentive for developing decision support system (DSS) that enables a fast prototyping of production flows in multi-project environment. The paper aims at providing a knowledge base approach allowing one to be independent of context or representation data as well as allowing for the design of an interactive and task-oriented DSS. The assumed knowledge base mode of specifying a production system leads to solving a decision problem formulated in terms of constraint satisfaction problem (CSP). Possible scenarios of the CSP decomposition as well as possibility of different programming languages application lead to a problem of searching for a distribution strategy that enables a real-time mode. A declarative form of the description of a multicriteria decision problem allows its implementation in constraint programming languages and facilitates the development of DSS. Illustrative example concerns optimal steelmaking process scheduling with constraints such as processing time, limited waiting time between adjacent tasks, and amount of resources allocated to tasks. Numerical experiments present the use of constraint programming approach, including various search strategies, to production planning and scheduling in the context of a metallurgical company.
Optimization by Heuristic procedure of Scheduling Constraints in Manufacturing System
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