Minimize Mean Tardiness Research Articles

Heuristics for Flowshop Scheduling Problems Minimizing Mean Tardiness

Several heuristics are presented for the flowshop scheduling problem with the objective of minimizing mean tardiness. We consider the cases in which job sequences on all machines are the same (permutation flowshop) and in which they may be different. For the former case, the various methods that have been devised for minimizing the makespan are modified for our objective, while the list scheduling algorithm is used for the latter case. These heuristics are tested and compared with each other on randomly-generated test problems.

Heuristics for Flowshop Scheduling Problems Minimizing Mean Tardiness

Heuristics for Flowshop Scheduling Problems Minimizing Mean Tardiness

Heuristics for Flowshop Scheduling Problems Minimizing Mean Tardiness

Heuristics for Flowshop Scheduling Problems Minimizing Mean Tardiness

A note on the equivalence of the Wilkerson-Irwin and modified due-data rules for the mean tardiness sequencing problem

We consider the problem of sequencing a set of simultaneously available jobs on a single-machine to minimize mean tardiness. Both the Wilkerson-Irwin (WI) and modified due-date (MDD) rules are effective heuristics for solving this problem. We show that the WI and MDD rules are in fact equivalent since both of them are based on the same local optimality condition for a pair of adjacent jobs. This provides some motivation to use the MDD and WI heuristics for the mean tardiness problem.

Heuristics for minimizing mean tardiness form parallel machines

The concept of parallel operations has been widely used in manufacturing and data processing. However, not many efficient methods have been proposed to reduce job tardiness. This article proposes an efficient heuristic to minimize the mean tardiness of a set of tasks with known processing times and due dates for single and m parallel machines. For the single-machine case, the proposed heuristic is compared with the well-known Wilkerson and Irwin algorithm; for the m parallel machine case, it is compared with an extension of the Wilkerson-Irwin algorithm. We also introduce a simple dispatching rule, and it is compared with some existing dispatching rules. The comprehensive simulation results show that the proposed heuristic performs better than the Wilkerson-Irwin algorithm at a significantly reduced computational time.

A Heuristic Solution Procedure to Minimize T on a Single Machine

In this paper, a heuristic procedure utilizing the adjacent pairwise interchange (API) methodology to minimize mean tardiness (\(\overline{T}\)) in single-machine scheduling is presented. Results indicate that it provides a much better solution than does the Wilkerson-Irwin heuristic algorithm, which also tries to minimize \(\overline{T}\). Experimental results suggest that the heuristic solution is not affected by problem size, which is important if larger problems are to be solved. Also, the heuristic is not affected by the tightness of due dates.

An experimental comparison of solution algorithms for the single‐machine tardiness problem

AbstractA basic problem in scheduling involves the sequencing of a set of independent tasks at a single facility with the objective of minimizing mean tardiness. Although the problem is relatively simple, the determination of an optimal sequence remains a challenging combinatorial problem. A number of algorithms have been developed for finding solutions, and this paper reports a comparative evaluation of these procedures. Computer programs for five separate algorithms were written and all were run on a data base designed to highlight computational differences. Optimizing algorithms developed by Emmons and by Srinivasan appeared to be particularly efficient in the comparative study.