Papers by Keyword: Production Scheduling

Abstract: Flow Shop Scheduling Problem is a class of scheduling problems with a work shop in which the flow control shall enable an appropriate sequencing for each job and for processing on a set of machines in compliance with given processing orders. In this paper, we propose a new heuristic algorithm based on the analysis and research of which problem, the new method introducing a evaluate mechanism of the relative position of any two jobs to the completion time, and the efficiency and performance has been improved .The result of simulation experiments shows that, our new heuristic algorithm has good performance, and the average quality and stability of scheduling sequences generated by new method is significantly better than other heuristic algorithm which has the same complexity.

Abstract: This paper focuses on the tube processing context in steel tube production and constructs a flexible job-shop scheduling problem (FJSP) model with consideration of the typical features and constraints. An evolutionary neighborhood search algorithm which consists of process consolidation (PC) strategy, production line adjustment (LA) strategy and elimination mechanism (EM) strategy is proposed. The computational tests show that the proposed algorithm has good performance.

Abstract: This research proposes a method of production scheduling using autonomous distributed systems. A concrete message protocol is proposed to realize the production scheduling which includes not only Machine but also Human and AGV scheduling. Moreover this method realizes real time scheduling and parallel scheduling. Therefore, a new structure of production scheduling is proposed, which can realize a change of the type of production scheduler to correspond with a type of production system.

Abstract: As the validity period of production data is short and data volume is big, a real-time data base is designed as the system database. Based on WEBGIS technique, Geographical Information System is designed, moreover, the production system, water flood system and power system are integrated into the system, thus laying foundations for production scheduling. Through analyzing real-time information stored in the database, early warning of well production and decision support can be provided for production managers, thus improving management level and promoting the coordinated development of the oilfield.

Abstract: In order to improve the inventory control efficiency and quality in manufacturing company, one production scheduling optimization method is put forward. Simulation of production model is firstly constructed, such as description of the production model, simulation data, machine processes and scheduling model. Moreover, Genetic Algorithm is applied to generate a production schedule for efficient running of machine. The simulation result is analyzed to verify the method by comparing product simulation with actual production.

Abstract: The flexible job shop scheduling problems are solved with the method of multi-objective program. In order to increase the stability of the solution, the concept of norm is led in objective functions, and new method to determine weights of the objective functions is presented. Finally, the optimal weights and the optimal solution of scheduling problem are obtained. Simulation results demonstrate the effectiveness of the proposed method.

Abstract: Based on explaining characteristics of aluminum production process and management, this paper built a production scheduling model of the aluminum casting with its equipment constrains and process constraints, discussed the optimization strategy of the production scheduling for aluminum casting.

Abstract: Most of the literature on scheduling problem only focuses on how to obtain the optimal schedule in static environment. However, when the schedule is carried out in job shop, it always meets with varied disturbances. These disturbances will make the schedule’s performance different from the pre-obtained schedule, and make the original schedule invalid. In this paper, the varied disturbances which always appear during the performance of schedule are studied. The repair methods responding to these disturbances are analyzed which are classified into three typical kinds. Using these three kinds of repair methods, the usual disturbances during scheduling can be repaired. And a right shift rescheduling method is proposed to reschedule the initial schedule.

Abstract: Multi-item, multi-period production systems are prevalent in traditional production and distribution settings. A dynamic lot size production scheduling model (DLSPM) for multi-Production/inventory item multi-period production system with parallel machines is proposed in this paper. A mathematical framework that extends the DLSPM to multi-Production/inventory item-multi-period production planning constrained by storage space was built. The criteria of DLSPM explore optimal production schedule with the constraints of inventory, backlogs, production and demand to minimize the total inventory costs over finite planning horizon. Demand analogous to a typical production environment considered includes dynamic deterministic and fuzzy demand. The model was tested with both deterministic and fuzzy demand spread over ten years, for five equal planning periods, with a two Production/inventory item and two parallel machine test bed. From the various demand types, several iterations (sub problems) were generated and optimality condition was then verified. To capture the imprecision that is often inherent in the estimated future demand, demand was specified by fuzzy numbers and modeled using the triangular membership function distribution. Centre of gravity defuzzification scheme was used within finite intervals to obtain defuzzified demand. Tora Operations Research software was used to run the model using a test problem. Computational results vindicate the robustness and flexibility of the approach based on the quality of the solutions obtained.

Abstract: A critical machine identification algorithm is proposed for the job shop scheduling problem in which the total tardiness must be minimized. An optimization-based procedure is devised to learn the distribution characteristics of critical machines in a specific scheduling instance. The proposed simulated annealing algorithm optimizes the scheduling problem after the capacity constraints for each machine are modified. A genetic algorithm based on combined dispatching rules is designed to verify the effectiveness of the proposed methodology.