Jeffrey E. Schaller

SCHEDULING A FLOWLINE MANUFACTURING CELL WITH SEQUENCE DEPENDENT FAMILY SETUP TIMES

This paper considers the problem of scheduling part families and jobs within each part family in a flowline manufacturing cell where the setup times for each family are sequence dependent and it is desired to minimize the makespan while processing parts (jobs) in each family together. Lower bounds on the optimal makespan value and eAcient heuristic algorithms for finding permutation schedules are proposed and empirically evaluated as to their eAectiveness in finding optimal permutation schedules. ” 2000 Elsevier Science B.V. All rights reserved.

A new lower bound for the flow shop group scheduling problem

This paper presents a new lower bound that is used to evaluate nodes in a branch and bound procedure for the flow shop group scheduling problem. This lower bound is compared to the one developed by [CIRP Annals, 25 (1976) 419] and tested on small randomly generated problems. A two-phased heuristic procedure is proposed which uses branch and bound in the first phase to develop a family sequence and then uses an interchange procedure in the second phase to develop job within family sequences. The heuristic procedure is tested on larger randomly generated problems.

Minimizing flow time in a flow-line manufacturing cell with family setup times

This paper considers the problem of scheduling part families and jobs within each part family in a flowline manufacturing cell with independent family setup times where parts (jobs) in each family are processed together. The objective is to minimize total flow time. A branch-and-bound algorithm capable of solving moderate sized problems is developed. Several heuristic algorithms are proposed and empirically evaluated as to their effectiveness and efficiency in finding optimal permutation schedules. These results show that several heuristic algorithms generate solutions that are better than those generated by an existing genetic algorithm.

Single machine scheduling with early and quadratic tardy penalties

This paper considers the problem of scheduling a single machine when the objective uses a penalty for each job that is equal to the earliness of the job plus the squared tardiness of the job. A timetabling algorithm is presented that inserts idle time into a sequence in order to minimize the objective considered. Optimal branch and bound algorithms are presented as well as efficient heuristic algorithms. The procedures are tested on randomly generated problems of varying numbers of jobs and due date tightness parameters. The results show that a branch and bound procedure can solve small and medium sized problems in a reasonable amount of time and that a simple descent procedure can quickly generate solutions that are close to optimal.

Improved heuristics for the single machine scheduling problem with linear early and quadratic tardy penalties

This paper considers the single machine scheduling problem with linear earliness and quadratic tardiness costs. The research on the version with an inserted idle time focused on an exact approach, while several heuristics were already proposed for the version with no idle time. These heuristics were then the basis for the development of new heuristic procedures for the version with idle time. Some improvement procedures were also considered. The new heuristics outperformed the existing procedures. A genetic algorithm provides the best results in terms of solution quality, but is computationally intensive. One of the backward scheduling dispatching rules provides results of similar quality and can quickly solve even large instances. The new heuristics were also applied, with the appropriate modifications, to the version with no idle time. Again, the new procedures provided better results than the existing heuristics. Therefore, the procedures developed in this paper are the new heuristics of choice for both versions of the considered problem. [Received 09 October 2008; Revised 02 February 2009; Accepted 20 February 2009]

Designing and redesigning cellular manufacturing systems to handle demand changes

This paper presents a model for cell formation that allows for period-to-period demand variability and considers the size of the cell when determining the cost to process each part. The model also allows the composition of a cell to be changed from period to period. Five heuristic procedures are presented and tested. The best procedure is also compared with two other traditional approaches. The results show that considering demand variability and changing the cell composition during the planning horizon can result in better solutions.

Note on minimizing total tardiness in a two-machine flowshop

This note considers the problem of sequencing jobs to minimize total tardiness in a two-machine flowshop. The note shows how three dominance conditions and a lower bound previously developed for this problem can be improved. The note also proposes a new dominance condition. A branch-and-bound algorithm is developed that uses the improvements and new dominance condition. The algorithm is tested on randomly generated problems and the results of the test show that the improvements and new dominance condition improves the branch-and-bound algorithms efficiency.

Minimizing the sum of squares lateness on a single machine

Abstract This paper proposes a new procedure that considers the use of inserted idle time to optimally solve the single machine scheduling problem where the objective is to minimize the sum of squares lateness. A heuristic procedure is also proposed for this problem. These procedures and an existing procedure developed by Gupta and Sen are tested using problems of various sizes in terms of the number of jobs to be scheduled and for different degrees of due date tightness. The performance measures are CPU time and sum of squares lateness of the solutions generated. The results show that a simple descent procedure yields very good results and is efficient even on large problems.

A comparison of heuristics for family and job scheduling in a flow-line manufacturing cell

This paper proposes new procedures for scheduling a flow-line manufacturing cell and compares the results obtained by using these new procedures to results obtained using procedures developed by Wemmerlov and Vakharia, Skorin-Kapov and Vakharia, and Sridhar and Rajendran. The procedures are evaluated on the basis of the makespans generated by solutions for test problems. The results show that the new procedures can efficiently generate good makespans and that results obtained by using the tabu search procedure developed by Skorin-Kapov and Vakharia can be improved if a starting set of job and family sequences is generated by one of the new procedures.

Single machine scheduling with family setups to minimize total earliness and tardiness

This paper considers the problem of scheduling a given number of jobs on a single machine to minimize total earliness and tardiness when family setup times exist. The paper proposes optimal branch-and-bound algorithms for both the group technology assumption and if the group technology assumption is removed. A heuristic algorithm is proposed to solve larger problems with the group technology assumption removed. The proposed algorithms were empirically evaluated on problems of various sizes and parameters. The paper also explores how the choice of procedure affects total earliness and tardiness if an implementation of lean production methods has resulted in a reduction in setup times. An important finding of these empirical investigations is that scheduling jobs by removing the group technology assumption can significantly reduce total earliness and tardiness.