A comparison of exhaustive and non-exhaustive group scheduling heuristics in a manufacturing cell

Previous group scheduling research has primarily focused on developing exhaustive two-stage heuristics in order to manage product flow through manufacturing cells. The objective of this paper is to present new, non-exhaustive heuristics and compare them with existing exhaustive heuristics in a job shop cell environment. Computer simulation is utilized to examine six non-exhaustive and six exhaustive heuristics under eight experimental conditions. The results indicate that although some non-exhaustive heuristics dominate the exhaustive heuristics on the average tardiness measure, the performance of exhaustive heuristics are generally superior to that of non-exhaustive heuristics. Furthermore, the performance of the exhaustive heuristics is more robust to the experimental factors.     

A comprehensive analysis of group scheduling heuristics in a job shop cell

This paper describes a broad-based simulation study of the performance of two-stage group scheduling heuristics in a job shop cell. The objective of this study was to examine the direct and interactive effects of a variety of shop factors on the performance of the best, previously reported, group scheduling heuristics. A set of traditional single-stage scheduling heuristics were examined as well. Shop factors considered include: setup to runtime ratio, cell load level and variability of inter-arrival times. An assumption common to group scheduling research which provides for an equal division of the part family into subfamilies is also examined. This is accomplished through the creation of an alternative scenario where the majority of the parts are assigned to one subfamily, i.e. one subfamily dominates the part family population. The effects of set up to runtime ratio and cell load have been examined in previous group scheduling research, but not in conjunction with the inter-arrival time variability factor. Further, no study has examined the impact of subfamily dominance on group scheduling heuristics in a full-scale simulation study. The results indicate that performance comparable to that of the two -stage heuristics can be obtained with the easily implementable single-stage heuristics when factors which lessen the impact of setup times are in place. In particular, the tardiness performance of two-stage scheduling heuristics deteriorates when subfamily dominance is in effect while the single-stage heuristics exhibit dramatic improvements in tardiness performance. Low setup to runtime ratio, shop load, and less variable inter-arrivals all induce dramatic performance gains across all measures among the single-stage heuristics, while yielding only marginal improvement in the performance of the two-stage heuristics. As a result, in many instances when combinations of these factors are in effect, the single-stage heuristics yield similar performance to the two-stage heuristics.     

Analysis of group technology scheduling heuristics

The need for increased productivity in small batch manufacturing has recently brought focus to the topics and concepts of group technology. The results of a simulation analysis of the use of three job shop simulation scheduling rules which focus on inducing efficiency in the shop is presented. Two of these rules show significant gains in efficiency and, unexpectedly, they also show significant gains in effectiveness. These rules, in effect, induce the efficiency gains expected with group technology implementation.     

Scheduling a flow-line manufacturing cell: a tabu search approach

The performance of two heuristic procedures for the scheduling of a flow-line manufacturing cell was compared. We propose a procedure based on a combinatorial search technique known as tabu search. The new procedure is compared with a heuristic based on simulated annealing which was proposed in earlier research. The scheduling problem addressed here differs from the traditional flow-shop scheduling problem in the sense that we are interested in sequencing part families (i.e. groups of jobs which share a similar setup) as well as individual jobs within each family. The results reveal that the tabu search heuristic outperforms the simulated annealing heuristic by generating 'better solutions' in less computation time.     

Cyclic scheduling heuristics for a re-entrant job shop manufacturing environment

Two efficient cyclic scheduling heuristics for re-entrant job shop environments were developed. Each heuristic generated an efficient and feasible cyclic production schedule for a job shop in which a single product was produced repetitively on a set of machines was to determine an efficient and feasible cyclic schedule which simultaneously minimized flow time and cycle time. The first heuristic considered a repetitive production re-entrant job shop with a predetermined sequence of operations on a single product with known processing times, set-up and material handling times. The second heuristic was a specialization of the first heuristic where the set-up for an operation could commence even while the preceding operation was in progress. These heuristics have been extensively tested and computational results are provided. Also, extensive analysis of worst-case and trade-offs between cycle time and flow time are provided. The results indicate that the proposed heuristics are robust and yield efficient and superior cyclic schedules with modest computational effort.     

Resource-constrained project scheduling: An evaluation of adaptive control schemes for parameterized sampling heuristics

For most computationally intractable problems there exists no simple heuristic that consistently outperforms all other heuristics. One remedy is to bundle simple heuristics into composite ones in a fixed and predetermined way. Adaptive control schemes take this approach one step further by dynamically combining algorithms. Several such algorithms have been proposed recently in various settings, yet an experimental investigation comparing them with other contemporary methods has been lacking. The aim here is to close this gap by a comprehensive computational study on the field of resource-constrained project scheduling. Also shown is how to improve effectiveness of the best algorithm by means of randomized sampling. Finally, revealed are several advantages of adaptive control schemes over other algorithms which facilitate the OR practitioner's task of designing good algorithms for newly arising problems.     

An improved branch and bound procedure for scheduling a flow line manufacturing cell

This paper presents a new branch and bound procedure for scheduling a flow-line manufacturing cell. This procedure and an existing procedure are tested on several problem sets with varying numbers of families, jobs and machines, and varying setup time distributions. The results show that the new procedure solves small problems dramatically faster than the existing procedure. Three heuristic procedures, based on the new branch and bound procedure, are developed. These heuristic procedures as well as a tabu search procedure are tested on problem sets with larger problem sizes. The results show that one of the new procedures generates solutions with improved makespans compared to the tabu search procedure.     

Tool handling and scheduling in a two-machine flexible manufacturing cell

In this paper we examine the issue of tool management in a flexible manufacturing cell. The type of system considered here is typical of mechanical manufacturing, in which large metallic parts are loaded on the machines and are not moved until processing completion. The architecture of the cell is characterized by the absence of on-board tool magazines on the machines. Although this permits the continuous maintenance and inspection of the tools and typically results in cost and workspace savings, it calls for more complex tool handling procedures. We present a heuristic to address the overall problem of assigning parts to machines, sequencing parts on each machine, and synchronizing tool movements. The results indicate that our method provides near-optimal solutions in terms of makespan and mean flow time. Further, we observe that the solution procedure is at least one order of magnitude faster than the approach currently used and also results in a much better mean flow time.     

Job shop scheduling heuristics and frequency of scheduling

This paper presents a job scheduling problem. Two important aspects are included in the subsequent analysis. The first is the dynamic nature whereby new jobs arrive to be included intermittently through time. The second is the uncertainty, or error in estimating process times, and the likelihood of machine breakdown. An experiment is presented which shows the performance of a number of heuristics in the form of dispatching disciplines under different scheduling conditions which are determined by the scheduling period and the level of uncertainty in the process times and machine breakdowns. Various different measures of performance which could be of importance to management are considered. These include mean ratio of flow time to process time, mean queueing time, mean lateness, percentage of jobs late and net CPU times required to generate schedules in the simulation process.

Results are presented showing the relationship between the performance of the heuristics relative to the different measures and the rescheduling period. These are discussed in the more general managerial context.     

Evaluation of heuristics for a class-constrained lot-to-order matching problem in semiconductor manufacturing

While semiconductors are being used in an increasing number of products, semiconductor manufacturers continually look for ways to make their processes more efficient. This paper will focus on an issue in the manufacturing process called the class-constrained lot-to-order matching problem (CLOMP), where individual lots of microprocessors are matched to customer orders, while seeking to optimize multiple objectives. Due to its complexity, the problem is decomposed into two stages—the first identifies which customer orders to fill while the second assigns specific lots to the chosen orders. We design an experiment with four first-stage sorting rules, four second-stage heuristics and two production cases. Based on our simulation results, this paper will recommend the first-stage sorting rule and second-stage heuristic which attain the best results with regards to our measures of effectiveness.     

Greedy heuristics for rapid scheduling of trains on a single track

This paper describes the core algorithm used in an implementation of a scheduler currently being installed in a major Asian railway. It extends previous work on a greedy heuristic for scheduling trains, to provide a powerful and practically useful method that is fast enough for real-time use in many cases. Real-world railway systems have constraints that do not fit easily into a simple mathematical formulation. The algorithm described here makes it straightforward to incorporate many such realistic features.     

On-line scheduling in a multi-cell flexible manufacturing system

This paper deals with on-line scheduling in a multi-cell flexible manufacturing system, operating in a produce-to-order environment. A two level distributed production control system (DPCS) is developed and tested through a simulation study. The DPCS allows autonomous and simultaneous operation of each cell-controller, utilizing only local and short term information as well as simple heuristic rules. Simulation experiments show that the proposed DPCS achieves good results in throughput, tardiness of orders and WIP inventory level and that it is robust to machine and handling device failures.     

An application of group technology concepts in shoe manufacturing

This study has concentrated on exploring the potential advantages of using group technology concepts in the Closing department of a shoe manufacturing factory. A simulation model of the factory has been developed to assist relevant experimentation and the results obtained have been evaluated by means of selected performance criteria encompassing throughout time, waiting time and delay ratio, machine and labour utilization.     

A heuristic for scheduling in flowshop and flowline-based manufacturing cell with multi-criteria

The problem of scheduling in flowshop and flowline-based manufacturing cell is considered with the bicriteria of minimizing makespan and total flowtime of jobs, The formulation of the scheduling problems for both the flowshop and the flowline-based manufacturing cell is first discussed. We then present the development of the proposed heuristic for flowshop scheduling. A heuristic preference relation is developed as the basis for the heuristic so that only the potential job interchanges are checked for possible improvement with respect to bicriteria, The proposed heuristic algorithm as well as the existing heuristic are evaluated in a large number of randomly generated large-sized flowshop problems. We also investigate the effectiveness of these heuristics with respect to the objective of minimizing total machine idletime. We then modify the proposed heuristic for scheduling in a cell, and evaluate its performance.     

Ordering scheduling problem in manufacturing systems

The problem of scheduling customer orders in the management of a large multi-product warehouse is addressed under realistic assumptions including rapidly changing data, uncertainties and unforeseen events. Simple flexible solution strategies are sought, in the sense that the scheduling problem should not be solved again from the beginning every time new information becomes available. Among the solution strategies, one is based on a few statistical assumptions about the random variables involved in the process: it exploits a stochastic version of the well-known duality principle for nonlinear programming and yields a number of interesting features.     

A scheduling problem in glass manufacturing

In this paper, a production scheduling problem in glass manufacturing is studied. The production facility consists of multiple identical production lines and each production line includes a number of serially arranged machines. The production is characterized by semi-ordered processing times in each product family, and the last machine in each production line is a bottleneck machine. Significant changeover times are required when products of different families are produced on a production line. The scheduling problem was modeled as a parallel no-delay flowshop scheduling problem (PNDFSP). The PNDFSP combines the parallel machine scheduling problem (PMSP) with the no-delay flowshop scheduling problem (NDFSP). While PMSP and NDFSP have received considerable attention in the literature, PNDFSP has not been well studied. A mixed-integer programming formulation is developed and an efficient heuristic algorithm is proposed. The sequential heuristic algorithm considers simultaneously the line changeover time, no-delay effect, and line utilization in assigning product families to the production lines. The computational results are reported.     

An experimental study of human decision-making in computer-based scheduling of flexible manufacturing system

This paper describes a study which explores human decision-making abilities in scheduling and dispatching of a flexible manufacturing system (FMS) An experiment is described, using an FMS, in which subjects make scheduling and dispatching decisions using a real-time interactive computer-simulation based system. The experimental results demonstrate that human decision-making is superior to general dispatching rules. An explanation of these results and an analysis of subjects' behaviour is presented in the light of information obtained from verbal protocol data     

A scheduling approach for a flexible manufacturing system

This paper discusses the scheduling problem of a particular flexible manufacturing system (FMS). The two main components of the FMS are a CNC turret lathe and a CNC machining centre. In the system a wide range of different jobs has to be processed. Each job consists of one or more processing operations on one or both machines. Important characteristics of the scheduling problem are sequence-dependent change-over times (on the turret lathe) and transfer times (on both machines and between the machines). The change-over times are caused by the need to exchange tools in the turret when a new part is going to be processed. The transfer times reflect the time needed to perform manual transportation and clamping activities between two subsequent processing (machining) operations of a part. In this paper a branch and bound algorithm is described based on an active schedule strategy. Solutions are compared to results obtained by a simple dispatching rule     

External partner selection using tabu search heuristics in distributed manufacturing

With every passing month, a number of new virtual enterprises emerge on the internet. Many companies have responded to the idea of distributed manufacturing in which the value adding activities comprising a finished product are dispersed geographically in a remote place. This study suggests an idea for selecting partners in a distributed manufacturing environment, which enables machining companies to share their capacities. A mathematical model is constructed to show how to minimize the sum of the operation and transportation costs based on alternative process plans considering several kinds of operation characteristics in the real world. Four heuristic algorithms are developed to get an optimal or near-optimal solution using tabu search since the model is proven NP-hard. Example problems are tested to illustrate their procedure and performance.