C Rajendran

We consider the flowshop scheduling problem with the twin-objective of minimizing makespan and total flowtime. We apply the Simulated Annealing (SA) technique to develop the proposed heuristic. Two new heuristics are proposed to provide the seed sequences for the SA heuristic. When compared with the existing heuristics, the proposed SA heuristic is found to perform much better. © 1994.

Most algorithms on flowshop scheduling assume that every stage has a single processor or machine only. With a view to achieve the practical objective of minimizing total flowtime, a branch-and-bound algorithm for obraining a permutation schedule for the multi-stage flowshop with parallel processorsis presented. Computational experience with the proposed algorithm and the existing single-processor algorithms revelas that most of the parallel-processor problems are solved faster and easier. The performance of the existing procedures is also evaluated in the parallel-processor environment. Since the flowshop scheduling problem is NP-complete, a heuristic algorithm for scheduling in a two-stage parallel-processor flowshop is proposed. The heuristic solutions, when compared with the optimal solutions given by the proposed branch-and-bound method, are found to be near-optimal. © 1992.

The problem of scheduling in a flowshop, where setup, processing and removal times are separable, is considered with the objective of minimizing makespan. Heuristic algorithms are developed by the introduction of simplifying assumptions into the scheduling problem under study. An improvement method is incorporated in the heuristics to enhance the quality of their solutions. The proposed heuristics and an existing heuristic are evaluated by a large number of randomly generated problems. The results of an extensive computational investigation for various values of parameters are presented. © 1997 Taylor & Francis Ltd.

This article deals with the development of a heuristic for scheduling in a flowshop with the objective of minimizing the makespan and maximum tardiness of a job. The heuristic makes use of the simulated annealing technique. The proposed heuristic is relatively evaluated against the existing heuristic for scheduling to minimize the weighted sum of the makespan and maximum tardiness of a job. The results of the computational evaluation reveal that the proposed heuristic performs better than the existing one. © 1999, Taylor & Francis Group, LLC. All rights reserved.

Most of the heuristics for flowshop scheduling aim at minimizing makespan. However, scheduling with multiple objectives, such as that of minimizing makespan, total flowtime and machine idletime, is more effective in reducing the total scheduling cost. In this article, we first address the problem of scheduling to minimize makespan and total flowtime, and propose a new heuristic algorithm. 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 these two objectives. The proposed as well as the existing heuristics are evaluated in a large number of randomly generated large-sized problems. The proposed heuristic algorithm is then extended to cover the problem of scheduling to minimize makespan, total flowtime and machine idletime. The results of the experimental investigation of the evaluation of this heuristic algorithm and the existing heuristic in meeting these objectives are also reported. It is found that both the proposed heuristics are more effective than the existing one for scheduling with multiple objectives. © 1995.

The problem of scheduling in a flowshop is considered, with the objective of minimizing the mean weighted tardiness. A case study is carried out in a drill-bit manufacturing industry. The problem encountered in the present study is different from the conventional flowshop scheduling problem in that the setup times are separated from process times and are sequence-dependent. A heuristic algorithm, based on simulated annealing (SA), is developed for scheduling in this flowshop. A method is presented for obtaining the initial seed sequence for the SA algorithm. A new exponential acceptance function and a new scheme for generating the neighbourhood, called the random insertion perturbation scheme (RIPS), are proposed. The stopping criteria make use of the temperature value and the value of freeze counter that is determined by the number of accepted and generated sequences. The SA heuristic is evaluated against existing heuristics and the results of computational evaluation reveal that the proposed heuristic performs much better. © 1997 Taylor & Francis Ltd.

This paper deals with the development and evaluation of heuristics for scheduling in a real-life flowshop. The case study differs from the conventional flowshop scheduling problem in that the setup times of jobs are separated from process times and are sequence-dependent. We present a heuristic algorithm that makes use of simulated annealing (SA) technique. We also present a perturbation scheme in the SA algorithm. The proposed and existing heuristics are evaluated for scheduling to minimize the maximum weighted tardiness of a job and total weighted tardiness of jobs. The results of the computational evaluation reveal that the proposed heuristic performs much better than the existing ones.