In this work we present a metaheuristic method based on tabu search for solving the permutation flow shop scheduling problem with sequence dependent setup times, with the objective of minimizing total weighted tardiness. The problem is well known for its practical applications and for the difficulty in obtaining good solutions. The tabu search method proposed is based on the insertion neighborh...

In this paper, we address a new integration of column generation and Lagrangian relaxation for solving flowshop scheduling problems to minimize the total weighted tardiness. In the proposed method, the initial columns are generated by using near-optimal dual variables for linear programming relaxation of Dantzig-Wolfe decomposition derived by the Lagrangian relaxation method. The column generat...

This paper develops a fuzzy multi-objective linear programming (FMOLP) model for solving a multiobjective single-machine scheduling problem. The proposed model attempts to minimize the total weighted tardiness andmakespan simultaneously. In this problem, a proposed FMOLPmethod is applied with respect to the overall acceptable degree of thedecisionmaker (DM) satisfaction. Anumber of numerical ex...

Appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. One type of scheduling problems is just-in-time (JIT) scheduling and in this area, motivated by JIT manufacturing, this study investigates a mathematical model for...

We address the parallel machine total weighted tardiness scheduling problem with release dates. We describe dominance rules and filtering methods for this problem. Most of them are adaptations of dominance rules based on solution methods for the single-machine problem. We show how it is possible to deduce whether or not certain jobs can be processed by a particular machine in a particular conte...

We consider a single-machine two-agent problem where the objective is to minimize a weighted combination of the total completion time and the total tardiness of jobs from the first agent given that no tardy jobs are allowed for the second agent. A branch-and-bound algorithm is developed to derive the optimal sequence and two simulated annealing heuristic algorithms are proposed to search for th...

Stochastic search algorithms are often robust, scalable problem solvers. In this paper, we concern ourselves with the class of stochastic search algorithms called stochastic sampling. Randomization in such a search framework can be an effective means of expanding search around a stochastic neighborhood of a strong domain heuristic. Specifically, we show that a value-biased approach can be more ...

Swarm Intelligence algorithms have proved to be very effective in solving problems on many aspects of Artificial Intelligence. This paper constitutes a first study of the recently proposed Unified Particle Swarm Optimization algorithm on scheduling problems. More specifically, the Single Machine Total Weighted Tardiness problem is considered, and tackled through a scheme that combines Unified P...