An efficient heuristic for scheduling on identical parallel machines to minimize total tardiness

Scheduling on parallel identical machines to minimize total tardiness

This paper focuses on the problem of scheduling n independent jobs on m identical parallel machines for the objective of minimizing total tardiness of the jobs. We develop dominance properties and lower bounds, and develop a branch and bound algorithm using these properties and lower bounds as well as upper bounds obtained from a heuristic algorithm. Computational experiments are performed on r...

Scheduling Identical Parallel Machines to Minimize Total Weighted Completion Time

A branch-and-bound algorithm with Lagrangian relaxation to minimize total tardiness on identical parallel machines

The purpose of this paper is to propose a new branch-and-bound algorithm for a class of scheduling problems to minimize total tardiness on identical parallel machines. In this algorithm, Lagrangian relaxation technique is applied to obtain a tight lower bound. In addition, the job dominance conditions for the single machine total tardiness problem are utilized for both restricting branches and ...

A Novel B and B Algorithm for a Unrelated Parallel Machine Scheduling Problem to Minimize the Total Weighted Tardiness

This paper presents a scheduling problem with unrelated parallel machines and sequencedependent setup times that minimizes the total weighted tardiness. A new branch-and-bound (B and B) algorithm is designed incorporating the lower and upper bounding schemes and several dominance properties. The lower and upper bounds are derived through an assignment problem and the composite dispatching rule ...

Minimizing total tardiness for scheduling identical parallel machines with family setups

This paper presents several procedures for scheduling identical parallel machines with family setups when the objective is to minimize total tardiness. These procedures are tested on several problem sets with varying numbers of families, jobs and machines, varying setup time distributions and various levels of due date tightness and variability. The results show that genetic algorithms are the ...