This paper presents a new mathematical model for a bi-objective job shop scheduling problem with sequencedependent setup times that minimizes the weighted mean completion time and the weighted mean tardiness time. For solving this multi-objective model, we develop a fuzzy multi-objective linear programming (FMOLP) model. In this problem, a proposed FMOLP method is applied with respect to the ov...

The parallel machine scheduling problem is an important and difficult problem to be considered in the real-world situations. Traditionally, this problem consists of the scheduling of a set of independent jobs on parallel machines with the aim of minimizing the maximum job completion. In today's manufacturing systems, in which both early and tardy finishing of job processing are undesired, the o...

We study the one-machine problem with release dates and we look at several objective functions including total (weighted) tardiness and total (weighted) completion time. We describe dominance rules for these criteria, as well as techniques for using these dominance rules to build heuristic solutions. We use them to improve certain well-known greedy heuristic algorithms from the literature. Fina...

In the present work, an industrial case study has been considered for multi-objective flow shop scheduling problem including the sequence dependent set up time. The multi-objectives include the minimization of sum of total weighted squared tardiness, total weighted squared earliness, makespan and number of tardy jobs. Industries can select the optimal sequence with respect to required objective...

We address the problem of determining schedules for static, single-machine scheduling problems where the objective is to minimize the sum of weighted tardiness and weighted earliness. We develop optimal and heuristic procedures for the special case of weights that are proportional to the processing times of the respective jobs. The optimal procedure uses dominance properties to reduce the numbe...

We study the one-machine scheduling problem with release dates and we look at several objective functions including total (weighted) tardiness and total (weighted) completion time. We describe dominance rules for these criteria, as well as techniques for using these dominance rules to build heuristic solutions. We use them to improve certain well-known greedy heuristic algorithms from the liter...

This paper addresses the one-machine scheduling problem with earliness-tardiness penalties. We propose a new branch-and-bound algorithm that can solve instances with up to 50 jobs and that can solve problems with even more general non-convex cost functions. The algorithm is based on the combination of a Lagrangean relaxation of resource constraints and new dominance rules.

This paper presents a simulated genetic algorithm (GA) model of scheduling the flow shop problem with reentrant jobs. The objective of this research is to minimize the weighted tardiness and makespan. The proposed model considers that the jobs with non-identical due dates are processed on the machines in the same order. Furthermore, the re-entrant jobs are stochastic as only some jobs are requi...

The single-machine early/tardy (E/T) scheduling problem is addressed in this research. The objective of this problem is to minimize the total amount of earliness and tardiness. Earliness and tardiness are weighted equally and the due date is common and large (unrestricted) for all jobs. Machine setup time is included and is considered sequence-dependent. When sequence-dependent setup times are ...