Modelistic Solution Approach for Flowshop Scheduling Problems on Makespan Criterion by Heuristics Models (original) (raw)
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— Production scheduling is generally considered to be the one of the most significant issue in the planning and operation of a manufacturing system. Better scheduling system has significant impact on cost reduction, increased productivity, customer satisfaction and overall competitive advantage. In addition, recent customer demand for high variety products has contributed to an increase in product complexity that further emphasizes the need for improved scheduling. Proficient scheduling leads to increase in capacity utilization efficiency and hence thereby reducing the time required to complete jobs and consequently increasing the profitability of an organization in present competitive environment. There are different systems of production scheduling including flowshop in which jobs are to be processed through series of machines for optimizing number of required performance measures. In modern manufacturing there is the trend of the development of the Computer Integrated Manufacturing (CIM is computerized integration of the manufacturing activities (Design, Planning, Scheduling and Control)) which produces right product(s) at right time to react quickly to the global competitive market demands. The productivity of CIM is highly depending upon the scheduling of Flexible Manufacturing System (FMS). Machine idle time can be decreased by sorting the makespan which results in the improvement in CIM productivity. Conventional methods of solving scheduling problems based on priority rules still result schedule, sometimes with idle times. To optimize these, this paper models the problem of a flowshop scheduling with the objective of minimizing the makespan. The work proposed here deal with the production planning problem of a flexible manufacturing system. This paper model the problem of a flowshop scheduling with the objective of minimizing the makespan. The objective is to minimize the makespan of batch-processing machines in a flowshop. The processing times and the sizes of the jobs are known and non-identical. The machines can process a batch as long as its capacity is not exceeded. The processing time of a batch is the longest processing time among all the jobs in that batch. The problem under study is non-polynomial (NP)-hard for make span objective. Consequently, comparisons based on RA's heuristics, CDS's heuristics are proposed in this work. Gantt chart is generated to verify the effectiveness of the proposed approaches.
Production scheduling is generally considered to be the one of the most significant issue in the planning and operation of a manufacturing system. Better scheduling system has significant impact on cost reduction, increased productivity, customer satisfaction and overall competitive advantage. In addition, recent customer demand for high variety products has contributed to an increase in product complexity that further emphasizes the need for improved scheduling. Proficient scheduling leads to increase in capacity utilization efficiency and hence thereby reducing the time required to complete jobs and consequently increasing the profitability of an organization in present competitive environment. There are different systems of production scheduling including flowshop in which jobs are to be processed through series of machines for optimizing number of required performance measures. In modern manufacturing there is the trend of the development of the Computer Integrated Manufacturing (CIM is computerized integration of the manufacturing activities (Design, Planning, Scheduling and Control)) which produces right product(s) at right time to react quickly to the global competitive market demands. The productivity of CIM is highly depending upon the scheduling of Flexible Manufacturing System (FMS). Machine idle time can be decreased by sorting the makespan which results in the improvement in CIM productivity. Conventional methods of solving scheduling problems based on priority rules still result schedule, sometimes with idle times. To optimize these, this paper models the problem of a flowshop scheduling with the objective of minimizing the makespan. The work proposed here deal with the production planning problem of a flexible manufacturing system. This paper model the problem of a flowshop scheduling with the objective of minimizing the makespan. The objective is to minimize the makespan of batch-processing machines in a flowshop. The processing times and the sizes of the jobs are known and non-identical. The machines can process a batch as long as its capacity is not exceeded. The processing time of a batch is the longest processing time among all the jobs in that batch. The problem under study is non-polynomial(NP)-hard for makespan objective. Consequently, comparisons based on RA's heuristics, CDS's heuristics are proposed in this work. Gantt chart is generated to verify the effectiveness of the proposed approaches. I. Introduction A Flexible manufacturing system (FMS) consists of a collection of numerically controlled machines with multifunction ability, an automatic material handling system and an online computer network. This network is capable of controlling and directing the whole system. An FMS combines the advantages of a traditional flow line and job-shop systems to meet the changing demands. Thus, it involves many problems, which can be divided into four stages: (a) design, (b) system setup , (c) scheduling and (d) control. FMS Scheduling system is one of the most important information-processing subsystems of CIM system. The productivity of CIM is highly depending upon the quality of FMS scheduling. The basic work of scheduler is to design an optimal FMS schedule according to a certain measure of performance, or scheduling criterion. This work focuses on productivity oriented-makespan criteria. Makespan is the time length from the starting of the first operation of the first demand to the finishing of the last operation of the last demand. The inherent efficiency of a flexible manufacturing system (FMS) combined with additional capabilities, can be harnessed by developing a suitable production plan. Machine scheduling problems arises in diverse areas such as flexible manufacturing system, production planning, computer design, logistics, communication etc. A common feature of many of these problems is that no efficient solution algorithm is known yet for solving it to optimality in polynomial time.
Flowshop Scheduling Problem for 10-Jobs, 10-Machines By Heuristics Models Using Makespan Criterion
In modern manufacturing there is the trend of the development of the Computer Integrated Manufacturing (CIM). CIM is computerized integration of the manufacturing activities (Design, Planning, Scheduling and Control) which produces right product(s) at right time to react quickly to the global competitive market demands. The productivity of CIM is highly depending upon the scheduling of Flexible Manufacturing System (FMS). Machine idle time can be decreased by sorting the make span which results in the improvement in CIM productivity. Conventional methods of solving scheduling problems based on priority rules still result schedule, sometimes with idle times. To optimize these, this paper models the problem of a flowshop scheduling with the objective of minimizing the makespan. The work proposed here deal with the production planning problem of a flexible manufacturing system. This paper models the problem of a flowshop scheduling with the objective of minimizing the make span. The objective is to minimize the makespan of batch-processing machines in a flowshop. The processing times and the sizes of the jobs are known and non-identical. The machines can process a batch as long as its capacity is not exceeded. The processing time of a batch is the longest processing time among all the jobs in that batch. The problem under study is NP-hard for makespan objective. Consequently, comparisons based on Palmer's and Gupta's heuristics are proposed in this work. Gantt chart is generated to verify the effectiveness of the proposed approaches.
In modern manufacturing there is the trend of the development of the Computer Integrated Manufacturing (CIM). CIM is computerized integration of the manufacturing activities (Design, Planning, Scheduling and Control) which produces right product(s) at right time to react quickly to the global competitive market demands. The productivity of CIM is highly depending upon the scheduling of Flexible Manufacturing System (FMS). Machine idle time can be decreased by sorting the make span which results in the improvement in CIM productivity. Conventional methods of solving scheduling problems based on priority rules still result schedule, sometimes with idle times. To optimize these, this papers model the problem of a flow shop scheduling with the objective of minimizing the makes pan. The work proposed here deal with the production planning problem of a flexible manufacturing system. The objective is to minimize the make span of batch-processing machines in a flow shop. The processing times and the sizes of the jobs are known and nonidentical. The machines can process a batch as long as its capacity is not exceeded. The processing time of a batch is the longest processing time among all the jobs in that batch. The problem under study is NP-hard for makespan objective. Consequently, comparisons based on Gupta’s heuristics, Palmer’s heuristics are proposed in this work. Gantt chart is generated to verify the effectiveness of the proposed approaches.
Computation of Makespan Using Genetic Algorithm in a Flowshop
This research paper addresses the scheduling problems with the primary objective of minimizing the makespan in a flow shop with 'N' jobs through 'M' machines. The EPDT (Heuristic approach) and BAT (Meta-Heuristic approach) heuristics are proposed to solve the flow shop scheduling problem in a modern manufacturing environment. These two algorithms are applied along with the Genetic Algorithm (GA) for the further improvement of results in achieving the minimal makespan. The performances of these newer heuristics are evaluated by solving the Taillard benchmark problems in MATLAB environment with various sizes of problems. The proposed GA applied EPDT heuristic and GA applied BAT meta-heuristic for the flow shop problems have been found very effective in solving scheduling problems and finding a better sequence which can reduce the makespan to a great extent. The improvement of EPDT and BAT were obtained by applying the GA yields superior results as well as these results...
Gantt Chart: An Important Tool of Management
International Journal of Innovative Technology and Exploring Engineering (IJITEE), 2019
The current paper aims to study on the important technique of time saving and money saving of the management. F.W. Taylor, Henry Fayol are the important contributors in the industrial development and growth. Their work in defining concept and principles of management is notable. Furthermore, Gantt's study is continued and he expressed scientific method of activity which can save time and money of an organization. F. W. Taylor worked on the planning and gave result that how planning helps to increase the work and quality of an organization. Henry Fayol defined fourteen Principles of the Management and Gantt declared activity chart. This chart is yet used in several industries as an ideal chart of activity plan. Therefore, current work focused on the Gantt chart and its importance in industries.
ICMIEE-PI-14016310 000 Minimization of Makespan in Flow Shop Scheduling Using Heuristics
2014
Production scheduling is one of the most significant issue in production and operations in any manufacturing system that has significant impact on cost reduction and increased productivity. Improper scheduling causes idle time for machines and hampers productivity that may cause an increased price of the product. So the main objective of this study is to minimize the makespan or total completion time. To do this study we have collected our data from Hatil complex limited, Mirpur, Dhaka, Bangladesh. This study presents Palmer’s heuristic, CDS heuristic, NEH algorithm for solving the flow shop scheduling problem to minimize the makespan. NEH yields more elaborate results as compared to Palmer and CDS heuristic. Grant chart is used to verify the effectiveness of heuristics. By applying these three techniques we have gotten an optimal result for each case. The use of these techniques makes it possible to generate a schedule that minimizes the makespan.
Application of Genetic Algorithm in Flowshop to Minimize Makespan
In this article presents an approach based on the application of Genetic Algorithm with the help of Exponential distribution factor (EPDT), to solve the problem of scheduling a permutation flow shop of n jobs on m machines when all jobs are available for processing. The objective is to minimize the makespan. Many researches planned various algorithms to achieve these objectives through an optimal sequence in a PFS. For identifying an optimal sequence for ‘n’ jobs in ‘m’ machines, sequences are to be worked. This planned heuristic approach, approximately solve the problem that consists in scheduling the jobs using Exponential Distribution factor which helps in developing a mathematical model with less computational instance. For the evaluation we use Ruben Ruiz well know standard problem using MAT LAB. The result shows that the planned algorithm is very effective and at the same time is easy to implement. Finally the results of newly planned heuristic are better when compare to the m...
A heuristic algorithm for scheduling in a flow shop environment to minimize makespan
Scheduling 'n' jobs on 'm' machines in a flow shop is NP-hard problem and places itself at prominent place in the area of production scheduling. The essence of any scheduling algorithm is to minimize the makespan in a flowshop environment. In this paper an attempt has been made to develop a heuristic algorithm, based on the reduced weightage of machines at each stage to generate different combination of 'm-1' sequences. The proposed heuristic has been tested on several benchmark problems of Taillard (1993) [Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64, 278-285.]. The performance of the proposed heuristic is compared with three well-known heuristics, namely Palmer's heuristic, Campbell's CDS heuristic, and Dannenbring's rapid access heuristic. Results are evaluated with the best-known upper-bound solutions and found better than the above three.
FlowOpt: Bridging the Gap Between Optimization Technology and Manufacturing Planners
2012
FlowOpt is an integrated collection of tools for workflow optimization in production environments. It was developed as a demonstration of advancements in the areas of modeling and optimization with the focus on simplifying the usage of the technology for end customers. The system consists of several interconnected modules. First, the user visually models a workflow describing the production of some item. Then the user specifies which items and how many of them should be produced (order management) and the system automatically generates a production schedule. This schedule is then visualized in the form of a Gantt chart where the user can arbitrarily modify the schedule. Finally, the system can analyze the schedule and suggest some improvements such as buying a new machine. Constraint satisfaction technology is the solving engine behind these modules.