Flowshop Scheduling Problem for 10-Jobs, 10-Machines By Heuristics Models Using Makespan Criterion (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 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.
— 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.
Flowshop Scheduling Problem for 10-Jobs, 10-Machines By
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.
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.
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.
A new heuristic for the flowshop scheduling problem to minimize makespan and maximum tardiness
International Journal of Production Research, 2009
In this paper a new heuristic for solving the flowshop scheduling problem which aims to minimising makespan and maximum tardiness is presented. The algorithm is then able to take into account the aforementioned performance measures, finding a set of non-dominated solutions representing the Pareto front. This method is based on the integration of two different techniques: a multi criteria decision making method and a constructive heuristic procedure developed for makespan minimisation in flowshop scheduling problems. In particular, the Technique for Order Preference by Similarity of Ideal Solution (TOPSIS) algorithm is integrated with the Nawaz-Enscore-Ham (NEH) heuristic to generate a set of potential scheduling solutions. To assess the proposed heuristic's performance a comparison with the best performing Multi Objective Genetic Local Search (MOGLS) algorithm proposed in literature is carried out. The test is executed on a large number of random problems characterized by different numbers of machines and jobs. The results show that the new heuristic frequently exceeds the MOGLS results in terms of both non-dominated solutions set quality and CPU time. In particular, the improvement becomes more and more significant as the number of jobs in the problem increases.
IAEME PUBLICATION, 2020
In this paper the authors investigate the problem of minimizing the Makespan using Heuristic approach. The author compared the result with the existing algorithms namely Palmer’s Heuristic(a slope order index), CDS Heuristic, NEH Heuristic algorithm, Gupta heuristic, RA (rapid access) Heuristic found in the literature and it was found that our algorithm perform superior than the other algorithms found in the literature
2012
This research deals with a flexible flowshop scheduling problem with arrival and delivery of jobs in groups and processing them individually. Due to the special characteristics of each job, only a subset of machines in each stage is eligible to process that job. The objective function deals with minimization of sum of the completion time of groups on one hand and minimization of sum of the differences between completion time of jobs and delivery time of the group containing that job (waiting period) on the other hand. The problem can be stated as FFc / rj , Mj / irreg which has many applications in production and service industries. A mathematical model is proposed, the problem is proved to be NPcomplete, and an effective heuristic method is presented to schedule the jobs efficiently. This algorithm can then be used within the body of any metaheuristic algorithm for solving the problem.
This paper deals with the heuristic solution of flexible flowshop scheduling problems with unrelated parallel machines. A setup time is necessary before starting the processing of a job, where the setup time depends on the previous job. No preemption of jobs is allowed. As objective function, this paper considers the minimization of the positively weighted convex sum of makespan and the number of tardy jobs. This paper develops some well-known constructive heuristics for the pure flowshop scheduling problems such as the algorithms given by Palmer (1965), Campbell, Dudek, and, as well as the insertion heuristic by Nawaz, to the flexible flowshop environment. By using one of these heuristics, the first stage sequence is generated. This sequence will then be used, in conjunction with either FIFO or permutation rules, to construct a schedule for the overall problem. The final solution is then the best schedule obtained by one of the two rules. Furthermore, some iterative heuristics such as a genetic algorithm and a simulated annealing approach are proposed to increase the quality of the constructive solution. Detailed computational results are presented to evaluate the efficiency of the heuristic algorithms. Detailed computational results with the algorithms are presented.