Single machine scheduling to minimize a modified total late work function with multiple due dates

Single Machine Scheduling to Minimize Total Weighted Late Work

Single Machine Group Scheduling with Setups to Minimize Total Tardiness

This paper considers the single machine scheduling problem with independent family (group) setup times where jobs in each family are processed together. A sequence independent setup is required to process a job from a different family. The objective is to minimize total tardiness. A mixed integer programming model capable of solving small sized problems is described. Several heuristic algorithm...

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...

Single Machine Scheduling with Distinct Due Dates under Fuzzy Environment

Single machine, distinct due dates, early/lately machine problem and fuzzy environment closely models the situation faced by ‘Just In Time’ manufacturing. The objective of this paper is to sequence the jobs on the machine, so that the total penalty cost be minimum. This cost is composed of the total earliness and the total tardiness cost. An algorithm is developed here to minimize the total pen...

Single-machine scheduling with waiting-time-dependent due dates

We consider a single-machine scheduling problem in which due dates are linear functions of the job waiting-times and the objective is to minimize the maximum lateness. An optimal sequence is constructed by implementing an index-based priority rule for a fixed value of the due date normalizing constant k. We determine in polynomial time all the k value ranges so that the optimal sequence remains...