The hybrid flow shop scheduling problem (original) (raw)
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Invited Review The hybrid flow shop scheduling problem
The scheduling of flow shops with multiple parallel machines per stage, usually referred to as the hybrid flow shop (HFS), is a complex combinatorial problem encountered in many real world applications. Given its importance and complexity, the HFS problem has been intensively studied. This paper presents a literature review on exact, heuristic and metaheuristic methods that have been proposed for its solution. The paper briefly discusses and reviews several variants of the HFS problem, each in turn considering different assumptions, constraints and objective functions. Research opportunities in HFS are also discussed.
World Academy of Science, Engineering and Technology, International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, 2010
This study compares three meta heuristics to minimize makespan (Cmax) for Hybrid Flow Shop (HFS) Scheduling Problem with Parallel Machines. This problem is known to be NP-Hard. This study proposes three algorithms among improvement heuristic searches which are: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). SA and TS are known as deterministic improvement heuristic search. GA is known as stochastic improvement heuristic search. A comprehensive comparison from these three improvement heuristic searches is presented. The results for the experiments conducted show that TS is effective and efficient to solve HFS scheduling problems. Keywords—Flow Shop, Genetic Algorithm, Simulated Annealing, Tabu Search.
Computers and Operations Research, Vol. 36, No.2, 2009, 358 - 378
This paper considers a flexible flow shop scheduling problem, where at least one production stage is made up of unrelated parallel machines. Moreover, sequence- and machine-dependent setup times are given. The objective is to find a schedule that minimizes a convex sum of makespan and the number of tardy jobs in a static flexible flow shop environment. For this problem, a 0-1 mixed integer program is formulated. The problem is however a combinatorial optimization problem which is too difficult to be solved optimally for large problem sizes, and hence heuristics are used to obtain good solutions in a reasonable time. The proposed constructive heuristics for sequencing the jobs start with the generation of the representatives of the operation time for each operation. Then some dispatching rules and flow shop makespan heuristics are developed. To improve the solutions obtained by the constructive algorithms, fast polynomial heuristic improvement algorithms based on shift moves and pairwise interchanges of jobs are applied. In addition, metaheuristics are suggested, namely simulated annealing, tabu search and genetic algorithms. The basic parameters of each metaheuristic are briefly discussed in this paper. The performance of the heuristics is compared relative to each other on a set of test problems with up to 50 jobs and 20 stages and with an optimal solution for small-size problems. We have found that among the constructive algorithms the insertion based approach is superior to the others, whereas the proposed simulated annealing algorithms are better than tabu search and genetic algorithms among the iterative metaheuristic algorithms.
A Heuristic for Group Scheduling the Multi-stage Hybrid Flow Shop Problems
According to the practical relevance, the Hybrid Flow Shop (HFS) has attracted many researchers recently. This paper addresses a special case of group scheduling problem in a multi-stage HFS with optimization of throughput related objectives. The aim of the work is to simplify the solution procedure through a heuristic approach to reach the optimal solution, i.e., minimal makespan with optimal flow parameters. The heuristic solution was tested with all possible group schedules encountered in the HFS problem to ensure the compatibility of the optimal solution and its consistency with the throughputs. The throughput related measures other than makespan such as queue status and machine utilization were considered to evaluate the performance of the heuristic. The heuristic performs well to reach the optimal solution with minimal makespan and queue status with effective machine utilization. A case study was done in a pulley manufacturing plant and a global solution was suggested.
Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion
In the paper, the flow-shop scheduling problem with parallel machines at each stage (machine center) is studied. For each job its release and due date as well as a processing time for its each operation are given. The scheduling criterion consists of three parts: the total weighted earliness, the total weighted tardiness and the total weighted waiting time. The criterion takes into account the costs of storing semi-manufactured products in the course of production and ready-made products as well as penalties for not meeting the deadlines stated in the conditions of the contract with customer. To solve the problem, three constructive algorithms and three metaheuristics (based one Tabu Search and Simulated Annealing techniques) are developed and experimentally analyzed. All the proposed algorithms operate on the notion of so-called operation processing order, i.e. the order of operations on each machine. We show that the problem of schedule construction on the base of a given operation processing order can be reduced to the linear programming task. We also propose some approximation algorithm for schedule construction and show the conditions of its optimality. r Hybrid flow-shop problems have received considerable attention from researchers during the last two decades. However, the scheduling criterion most frequently considered in those papers was the maximum completion time, see , , , and . Furthermore, these studies propose either an exact algorithm, which can solve only up to moderate size problem instances, or different types of heuristic and approximation algorithms .
Multicriteria Hybrid Flow Shop Scheduling Problem: Literature Review, Analysis, and Future Research
Independent Journal of Management Production, 2014
This research focuses on the Hybrid Flow Shop production scheduling problem, which is one of the most difficult problems to solve. The literature points to several studies that focus the Hybrid Flow Shop scheduling problem with monocriteria functions. Despite of the fact that, many real world problems involve several objective functions, they can often compete and conflict, leading researchers to concentrate their efforts on the development of methods that take this variant into consideration. The goal of the study is to review and analyze the methods in order to solve the Hybrid Flow Shop production scheduling problem with multicriteria functions in the literature. The analyses were performed using several papers that have been published over the years, also the parallel machines types, the approach used to develop solution methods, the type of method develop, the objective function,
A heuristic method for two-stage hybrid flow shop with dedicated machines
2013
Two-stage hybrid flow shop Dedicated machine Branch and bound Makespan Heuristic a b s t r a c t This paper considers a two-stage hybrid flow shop scheduling problem with dedicated machines, in which the first stage contains a single common critical machine, and the second stage contains several dedicated machines. Each job must be first processed on the critical machine in stage one and depending on the job type, the job will be further processed on the dedicated machine of its type in stage two. The objective is to minimize the makespan. To solve the problem, a heuristic method based on branch and bound (B&B) algorithm is proposed. Several lower bounds are derived and four constructive heuristics are used to obtain initial upper bounds. Then, three dominance properties are employed to enhance the performance of the proposed heuristic method. Extensive computational experiments on two different problem categories each with various problem configurations are conducted. The results show that the proposed heuristic method can produce very close-to-optimal schedules for problems up to 100 jobs and five dedicated machines within 60 s. The comparisons with solutions of two other meta-heuristic methods also prove the better performance of the proposed heuristic method.
Computers & Operations Research, 2010
In this paper, an extensive review of recently published papers on hybrid flow shop (HFS) scheduling problems is presented. The papers are classified first according to the HFS characteristics and production limitations considered in the respective papers. This represents a new approach to the classification of papers in the HFS environment. Second, the papers have been classified according to the solution approach proposed. These two classification categories give a comprehensive overview on the state of the art of the problem and can guide the reader with respect to future research work.