A survey of algorithms for the single machine total weighted tardiness scheduling problem

Minimizing Total Weighted Tardiness with Drop Dead Dates in Single Machine Scheduling Problem

  This paper deals with minimization of tardiness in single machine scheduling problem when each job has two different due-dates i.e. ordinary due-date and drop dead date. The drop dead date is the date in which jobs’ weights rise sharply or the customer cancels the order. A linear programming formulation is developed for the problem and since the problem is known to be NP-hard, three heuristic...

Beam search algorithms for the single machine total weighted tardiness scheduling problem with sequence-dependent setups

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 ...

New Instances for the Single Machine Total Weighted Tardiness Problem

Previous research in the single machine total weighted tardiness problem (SMTWTP) has led to the proposition of effective local search strategies. At least existing benchmark instances from the literature do not pose a challenge for state-of-the-art algorithms. This paper describes the proposition of two classes of novel instances for the single machine total weighted tardiness problem. In resp...

A Cluster-based Evolutionary Algorithm for the Single Machine Total Weighted Tardiness-scheduling Problem

In this paper a new evolutionary algorithm is described for the single machine total weighted tardiness problem. The operation of this method can be divided in three stages: a cluster forming and two local search stages. In the first stage it approaches some locally optimal solutions by grouping based on similarity. In the second stage it improves the accuracy of the approximation of the soluti...