Gyártási műveletek illeszkedésén alapuló heurisztikus ütemező módszer alkalmazása szalagrendszerű gyártásban

A gyártásütemezés feladata a múlt század közepe óta foglalkoztatja a kutatókat. A magas költségű gyártósorok és berendezések optimális kihasználása és a megrendelések minél gyorsabb kiszolgálása elengedhetetlenné teszi ezen módszerek használatát. Jelen cikkben a gyártástervezés egy speciális területével, a szalagrendszerű gyártással foglalkozunk. Egymást követő gyártási műveletek átfutási idejének összehasonlításával egy egyszerű illeszkedés alapú heurisztikus megközelítést mutatunk be. Módszerünk épít továbbá az utazó ügynök probléma egy korszerű megoldására is. Az ütemezés optimalizálásánál célfüggvénynek a teljes átfutási idő minimalizálását választottuk. Megoldásunk hatékonyságát annak működési paramétereinek finomhangolásával is növeltük illetve részletesen vizsgáltuk az egyes paraméterek végeredményre gyakorolt hatását. Megközelítésünk jóságát a szakirodalomban elterjedt mintafeladatok megoldásával bizonyítottuk

Variants of the Two Machine Flow Shop Problem connected with factorization of matrix functions

In this paper we consider a number of variants of the Two Machine Flow Shop Problem. In these variants the makespan is given and the problem is to find a schedule that meets this makespan, thereby minimizing the infeasibilities of the jobs in a prescribed sense: In the max-variant the maximum infeasibility of the jobs is to be minimized, whereas in the sum-variant the objective is to minimize the sum of the infeasibilities of the jobs. For both variants observations about the structure of the optimal schedules are presented. In particular, it is proved that every instance of these problems has an optimal permutation schedule. It is also shown that the max-variant can be solved by Johnson's Rule. For the sum-variant this is not the case: For solving this problem to optimality something quite different is necessary. Both variants are connected with factorization problems for certain rational matrix functions. The factorizations involved are optimal in some sense and generalize the notion of complete factorization. In this way a connection is established between job scheduling theory on one hand, and mathematical systems theory on the other

The Legacy of Taylor, Gantt, and Johnson: How to Improve Production Scheduling

This manuscript has been accepted for publication in the International Journal of Operations and Quantitative Management.The challenge of improving production scheduling has inspired many different approaches. This paper examines the key contributions of three individuals who improved production scheduling: Frederick Taylor, who defined the key planning functions and created a planning office; Henry Gantt, who provided useful charts to improve scheduling decision-making, and S.M. Johnson, who initiated the mathematical analysis of production scheduling problems. The paper presents an integrative strategy to improve production scheduling that synthesizes these complementary approaches. Finally, the paper discusses the soundness of this approach and its implications on OR research, education, and practice

Linking Scheduling Criteria to Shop Floor Performance in Permutation Flowshops

The goal of manufacturing scheduling is to allocate a set of jobs to the machines in the shop so these jobs are processed according to a given criterion (or set of criteria). Such criteria are based on properties of the jobs to be scheduled (e.g., their completion times, due dates); so it is not clear how these (short-term) criteria impact on (long-term) shop floor performance measures. In this paper, we analyse the connection between the usual scheduling criteria employed as objectives in flowshop scheduling (e.g., makespan or idle time), and customary shop floor performance measures (e.g., work-in-process and throughput). Two of these linkages can be theoretically predicted (i.e., makespan and throughput as well as completion time and average cycle time), and the other such relationships should be discovered on a numerical/empirical basis. In order to do so, we set up an experimental analysis consisting in finding optimal (or good) schedules under several scheduling criteria, and then computing how these schedules perform in terms of the different shop floor performance measures for several instance sizes and for different structures of processing times. Results indicate that makespan only performs well with respect to throughput, and that one formulation of idle times obtains nearly as good results as makespan, while outperforming it in terms of average cycle time and work in process. Similarly, minimisation of completion time seems to be quite balanced in terms of shop floor performance, although it does not aim exactly at work-in-process minimisation, as some literature suggests. Finally, the experiments show that some of the existing scheduling criteria are poorly related to the shop floor performance measures under consideration. These results may help to better understand the impact of scheduling on flowshop performance, so scheduling research may be more geared towards shop floor performance, which is sometimes suggested as a cause for the lack of applicability of some scheduling models in manufacturing

Mathematical Model and Meta-Heuristic Algorithm for Dual Resource Constrained Hybrid Flow-Shop Scheduling Problem with Job Rejection

In the real world, firms with hybrid flow-shop manufacturing environment generally facethe human resource constraint, salary cost increasment and efforts to make better use oflabor, in addition to machine constraint. Given the limitations of these resources, productdelivery requierements to customers have made the job rejection essential in order to meetdistinct customer requirements. Therefore, this research has studied the dual resourceconstrained hybrid flow-shop scheduling problem with job rejection in order to minimizethe total net cost (the sum of the total rejection cost and the total tardiness cost of jobs)which is widely used in many industries. In this article, a mixed integer linear programmingmodel has developed for the research problem. In addition, an improved sooty ternoptimization algorithm (ISTOA) has proposed to solve the large-sized problems as well asa decoding method due to the NP-hardness of the problem. In order to evaluate theproposed optimization algorithm, five well-known algorithms in the literature including(immunoglobulin-based artificial immune system (IAIS), genetic algorithm (GA), discreteartificial bee colony (DABC), improved fruit fly optimization (IFFO), effective modifiedmigrating birds optimization (EMBO)) have adapted with the proposed problem. Finally,the performance of the proposed optimization algorithm has investigated against theadapted algorithms. Results and evaluations show the good performance of the improvedsooty tern optimization algorithm

A Branch and Bound Method for Sum of Completion Permutation Flow Shop

We present a new branch and bound algorithm for solving three machine permutation flow shop problem where the optimization criterion is the minimization of sum of completion times of all the jobs. The permutation flow shop problem (F||∑Ci ) belongs to the class of NP-hard problems; finding the optimal solution is thus expected to be highly computational. For each solution our scheme gives an approximation ratio and finds near optimal solutions. Computational results for up to 20 jobs are given for 3 machine flow shop problem when the objective is minimizing the sum of completion times. The thesis also discusses a number of related but easier flow shop problems where polynomial optimization algorithms exist

Minimizing the makespan in a flexible flowshop with sequence dependent setup times, uniform machines, and limited buffers

This research addresses the problem of minimizing the makespan in a flexible flowshop with sequence dependent setup times, uniform machines, and limited buffers. A mathematical model was developed to solve this problem. The problem is NP-Hard in the strong sense and only very small problems could be solved optimally. For exact methods, the computation times are long and not practical even when the problems are relatively small. Two construction heuristics were developed that could find solutions quickly. Also a simulated annealing heuristic was constructed that improved the solutions obtained from the construction heuristics. The combined heuristics could compute a good solution in a short amount of time. The heuristics were tested in three different environments: 3 stages, 4 stages, and 5 stages. To assess the quality of the solutions, a lower bound and two simple heuristics were generated for comparison purposes. The proposed heuristics showed steady improvement over the simple heuristics. When compared to the lower bounds, the heuristics performed well for the smaller environment, but the performance quality decreased as the number of stages increased. The combination of these heuristics defiantly shows promise for solving the problem