https://ira.lib.polyu.edu.hk/bitstream/10397/1269/1/SetupSurvey-2006%28June-19%29.pdf

A survey of scheduling problems with setup times or costs

A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times

The significance of reducing setup times/setup costs

The evolution of cell formation problem methodologies based on recent studies (1997–2008): Review and directions for future research

In this work three genetic algorithms are presented for the permutation flowshop scheduling problem with total tardiness minimisation criterion. The algorithms include advanced techniques like path relinking, local search and a procedure to control the diversity of the population. We also include a speed up procedure in order to reduce the computational effort needed for the local search technique, which results in large CPU time savings. A complete calibration of the different parameters and operators of the proposed algorithms by means of a design of experiments approach is also given. We carry out a comparative evaluation with the best methods that can be found in the literature for the total tardiness objective, and with adaptations of other state-of-the-art methods originally proposed for other objectives, mainly makespan. All the methods have been implemented with and without the speed up procedure in order to test its effect. The results show that the proposed algorithms are very effective, outperforming the remaining methods of the comparison by a considerable margin.

/pdf/genetic-algorithms-with-path-relinking-for-the-minimum-5c5zooenpn.pdf

Genetic algorithms with path relinking for the minimum tardiness permutation flowshop problem

This research deals with scheduling jobs on unrelated parallel machines with auxiliary equipment constraints Each job has a due date and requires a single operation A setup for dies is incurred if there is a switch from processing one type of job to another type For a die type, the number of dies is limited Due to the attributes of the machines and the fitness of dies to each, the processing time for a job depends on the machine on which the job is processed, each job being restricted to processing on certain machines In this paper, an effective heuristic based on threshold-accepting methods, tabu lists, and improvement procedures is proposed to minimize total tardiness An extensive experiment is conducted to evaluate the computational characteristics of the proposed heuristic Computational experiences demonstrate that the proposed heuristic is capable of obtaining optimal solutions for small-sized problems, and significantly outperforms an ATCS procedure and a simulated annealing method for problems in larger sizes

Total tardiness minimization on unrelated parallel machine scheduling with auxiliary equipment constraints

The cell formation problem determines the decomposition of the manufacturing cells of a production system in which machines are assigned to these cells to process one or more part families so that each cell is operated independently and the intercellular flows are minimised or the number of parts flow processed within cells is maximised. In this paper, a tabu search heuristic—TSCF—that consists of dynamic tabu tenure with a long-term memory mechanism is presented to solve the cell formation problem. Test problems adopted from the literature and generated randomly are used to evaluate the performance of the proposed algorithm. In addition, two methods for quickly generating the initial solutions are proposed, namely the group-and-assign (GAA) method, and the random approach. Computational results indicate that the GAA method, accompanied by the TSCF algorithm can produce optimal solutions in less than or equal to 0.005 s for all small- and medium-sized problems. The proposed algorithm should thus be useful to both practitioners and researchers.

A tabu search approach to the cell formation problem

For the last thirty years, in job shop scheduling, the setup times of operations have been either ignored or combined with their corresponding processing times, independent setups, to simplify the work of model construction. However, in practice, the setup times of an operation are usually considered be sequence-dependent. Moreover, the performance of a scheduling system is not evaluated to satisfy a single objective, but to obtain a trade-off solution regarding multiple objectives. Therefore, this paper investigates job shop scheduling problems with re-entrant operations where the setup times, which vary according to the preceding operation which is processed on the same machine, and which can be separated from their corresponding processing times, cannot be omitted. Three practical performance measures – minimum total job flow time, minimum total job tardiness and minimum machine idle time – are considered. An integer programming model is first developed to optimise each single objective and an acceptable trade-off schedule, which makes use of a multiple-decision-making technique, the global criterion method, is obtained by evaluating three objectives simultaneously .

Mathematical modelling of multi-objective job shop scheduling with dependent setups and re-entrant operations

Hybrid heuristic algorithms are proposed for the nesting of two-dimensional rectangular parts in multiple plates. The nesting algorithm of Babu and Babu is first modified and a new heuristic nesting algorithm, IBH, is proposed to utilize the material plate further. IBH is then combined in a meta-heuristic approach, simulated annealing. The proposed hybrid algorithms can then be extended to solve the nesting problem involving irregular parts by embedding irregular parts to rectangles. One problem arises in this 'irregular-to-rectangular' process, i.e. conversion of demands of the original irregular parts into demands of the embedding rectangles. A greedy heuristic rule is therefore presented to determine the number of embedding rectangles of different types to be used in order to maximize the utilization of the material plate given that the demand of each irregular part must be satisfied. Promising computational results are obtained and reported by running examples from the literature and data relevant to ...

Nesting of two-dimensional parts in multiple plates using hybrid algorithm

This paper considers the cell formation problem in which alternative process plans exist for each part. A three-stage algorithm decomposing the original problem into three subproblems, i.e., process plan selection, parts assignment, and machines assignment problems, respectively, is proposed to solve this problem. Test problems, both from the literature and those generated in this study, are used to evaluate the performance of the proposed algorithm. The proposed algorithm can very efficiently find good-quality solutions and should thus be useful to practitioners and researchers.

Tai-Hsi Wu

Papers

Total tardiness minimization on unrelated parallel machine scheduling with auxiliary equipment constraints

A tabu search approach to the cell formation problem

Mathematical modelling of multi-objective job shop scheduling with dependent setups and re-entrant operations

Nesting of two-dimensional parts in multiple plates using hybrid algorithm

A decomposition approach to the cell formation problem with alternative process plans