Flexible job shop scheduling under availability constraints (original) (raw)
Related papers
2019
Co-Authorship I hereby declare that this thesis incorporates material that is result of joint research of the author and his supervisors Prof. Ahmed Azab and Prof. Fazle Baki. Chapters 3, 4, 5, 6, 7 of the thesis was co-authored with Prof. Ahmed Azab and Prof. Fazle Baki. In all the cases, the key ideas, primary contributions, experimental design, data analysis, interpretation and writing were performed by the author; Prof. Ahmed Azab and Prof. Fazle Baki provided feedback on refinement of ideas and editing of the manuscript. This joint research has been submitted to Journals and Conferences that are listed below. I am aware of the University of Windsor Senate Policy on Authorship, and I certify that I have properly acknowledged the contribution of other researchers to my thesis, and have obtained written permission from Prof. Ahmed Azab and Prof. Fazle Baki to include the above material(s) in my thesis. I certify that, with the above qualification, this thesis, and the research to which it refers, is the product of my own work. II.
An efficient algorithm for solving the flexible job shop scheduling problem
To investigate the efficiency of a discretization procedure utilizing a time-indexed mathematical optimization model for finding accurate solutions to flexible job shop scheduling problems considering objectives comprising makespan and tardiness, respectively. Design/methodology/approach A time-indexed mixed integer programming model is used to find solutions by iteratively employing time steps of decreasing length. The solutions and computation times are compared with results from a known benchmark formulation and an alternative model. Findings The proposed method finds significantly better solutions for the largest instances within the same time frame. Both the other models are better choices for some smaller instances, which is expected since the new method is designed for larger problems. Only our alternative model is able to solve two of the largest instances when minimizing the tardiness. Research limitations/implications Interesting future research topics include the introduction of constraints representing other relevant entities such as the availability of tools and fixtures, and the scheduling of maintenance activities and personnel. Practical implications Real cases of flexible job shop problems typically yield very large models. Since the new procedure quickly finds solutions of good quality to such instances, our findings imply that the new procedure is beneficially utilized for scheduling real flexible job shops. Original/value We show that real flexible job shop problems can be solved through the solution of a series of carefully formulated discretized mathematical optimization models.
Flexible job shop scheduling with overlapping in operations
Applied Mathematical Modelling, 2009
In this paper, flexible job shop scheduling problem with a new approach, overlapping in operations, is discussed. In many flexible job shops, a customer demand can be released more than one for each job, where demand determines the quantity of each finished job ordered by a customer. In these models each job has a demand more than one. This assumption is an important and practical issue for many flexible job shops such as petrochemical industries. To consider this assumption, we use a new approach, named overlapping in operations. In this approach, embedded operations of each job can be performed due to overlap considerations in which each operation may be overlapped with the others because of its nature. The overlapping is limited by structural constraints, such as the dimensions of the box to be packed or the capacity of the container used to move the pieces from one machine to the next. Since this problem is well known as NP-Hard class, a hierarchical approach used simulated annealing algorithm is developed to solve large problem instances. Moreover, a mixed integer linear programming (MILP) method is presented. To evaluate the validity of the proposed SA algorithm, the results are compared with the optimal solution obtained with the traditional optimization technique (The Branch and Bound method). The computational results validate the efficiency and effectiveness of the proposed algorithm. Also the computational results show that the overlapping considering can improve the makespan and machines utilization measures. So the proposed algorithm can be applied easily in real factory conditions and for the large size problems and it should thus be useful to both practitioners and researchers.
A research survey: review of flexible job shop scheduling techniques
In the last 25 years, extensive research has been carried out addressing the flexible job shop scheduling (JSS) problem. A variety of techniques ranging from exact methods to hybrid techniques have been used in this research. The paper aims at presenting the development of flexible JSS and a consolidated survey of various techniques that have been employed since 1990 for problem resolution. The paper comprises evaluation of publications and research methods used in various research papers. Finally, conclusions are drawn based on performed survey results.
IFAC-PapersOnLine, 2015
This paper deals with the cyclic scheduling of flexible job-shop with time window constraints and resource capacity constraints. For time window constraints, the duration for processing products on machines and the duration for translating products from one machine to another by transfers are taken into account; for the resource capacity constraints, the confined operation space of machines and the length-limited transfers are considered. The example applied in this paper is a flexible job-shop of two kinds of products with demanded products ratio, which can be described as a P-time strongly connected event graph (PTSCEG). The mixed integer programming (MIP) is used to give proper constraints of token's cyclic activities in PTSCEG. Using CPLEX 12.5, the computational time is acceptable for 1cyclic scheduling of small or medium sized cases.
This paper presents an investigation of scheduling procedures to seek the minimum of a positively weighted convex sum of makespan and the number of tardy jobs in a static flexible flow shop scheduling environment. The flexible flow shop problem is a scheduling of jobs in a flow shop environment consisting of series of production stages, some of which may have only one machine, but at least one stage must have multiple machines. In addition, sequence -and machinedependent setup times are considered. No preemption of jobs is allowed. Some dispatching rules and flow shop makespan heuristics are adapted for sequencing in the flexible flow shop problem.
Three Algorithms for Flexible Flow-shop Scheduling
American Journal of Applied Sciences, 2007
Scheduling is an important process widely used in manufacturing, production, management, computer science, and so on. Appropriate scheduling can reduce material handling costs and time. Finding good schedules for given sets of jobs can thus help factory supervisors effectively control job flows and provide solutions for job sequencing. In simple flow shop problems, each machine operation center includes just one machine. If at least one machine center includes more than one machine, the scheduling problem becomes a flexible flow-shop problem. Flexible flow shops are thus generalization of simple flow shops. In this paper, we propose three algorithms to solve flexible flow-shop problems of more than two machine centers. The first one extends Sriskandarajah and Sethi's method by combining both the LPT and the search-and-prune approaches to get a nearly optimal makespan. It is suitable for a medium-sized number of jobs. The second one is an optimal algorithm, entirely using the search-and-prune technique. It can work only when the job number is small. The third one is similar to the first one, except that it uses Petrov's approach (PT) to deal with job sequencing instead of searchand-prune. It can get a polynomial time complexity, thus being more suitable for real applications than the other two. Experiments are also made to compare the three proposed algorithms. A trade-off can thus be achieved between accuracy and time complexity.
Survey of Job Shop Scheduling Techniques
2008
Scheduling has been defined as "the art of assigning resources to tasks in order to insure the termination of these tasks in a reasonable amount of time " (1). According to French (2), the general problem is to find a sequence, in which the jobs (e.g., a basic task) pass between the resources (e.g., machines), which is a feasible schedule, and optimal with respect to some performance criterion. Graves (3) introduced a functional classification scheme for scheduling problems. This scheme categorizes problems using the following dimensions: 1. Requirement generation, 2. Processing complexity, 3. Scheduling criteria, 4. Parameter variability, 5. Scheduling environment. Based on requirements generation, a manufacturing shop can be classified as an open shop or a closed shop. An open shop is "build to order", and no inventory is stocked. In a closed shop the orders are filled from existing inventory. Processing complexity refers to the number of processing steps and w...
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 Genetic Algorithm-Based Approach for Flexible Job Shop Scheduling
2011
Flexible job shop scheduling is a hard combinatorial optimization problem. This paper introduces a simulation-based Genetic Algorithm approach to solve flexible job shop scheduling problem. Four manufacturing scenarios have been considered to access the performance of a job shop with objective to minimize mean tardiness, mean flow time and makespan. Results show that multiple process plans performs better than single process plan for each job type and if only single process plan is made available, then process plan selected on the basis of minimum production time criterion yields better results than other criterion of randomly selected process plan and minimum number of set-ups. Moreover, embedding restart scheme into regular Genetic Algorithm results improvement in the fitness value.