Minimizing Total Tardiness: A Case Study in an Autoparts Factory (original) (raw)
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A New Algorithm for Solving the Single Machine Total Tardiness Scheduling Problem
We are analyzing a multifunctional machine and the set of tasks to be performed by the machine. Each task has to be finished before a given due date. We are interested in finding a schedule of the tasks in such a way that the machine complies with the due dates. The problem is formulated as a minimum total tardiness scheduling problem. An heuristic algorithm for the problem is proposed. Finally, a comparative computational experience between this algorithm and other heuristic and exact algorithms is reported. Key-Words: scheduling, tardiness problem, single machine, exact and heuristic algorithms CSCC99, pp.2851-2858
Applied Computer Systems
A problem of minimizing the total weighted tardiness in the preemptive single machine scheduling for discrete manufacturing is considered. A hyper-heuristic is presented, which is composed of 24 various heuristics, to find an approximately optimal schedule whenever finding the exact solution is practically intractable. The three heuristics are based on the well-known rules, whereas the 21 heuristics are introduced first. Therefore, the hyper-heuristic selects the best heuristic schedule among 24 schedule versions, whose total weighted tardiness is minimal. Each of the 24 heuristics can solely produce a schedule which is the best one for a given scheduling problem. Despite the percentage of zero gap instances decreases as the greater number of jobs is scheduled, the average and maximal gaps decrease as well. In particular, the percentage is not less than 80 % when up to 10 jobs are scheduled. The average gap calculated over nonzero gaps does not exceed 4 % in the case of scheduling 7...
Improved heuristics for the early/tardy scheduling problem with no idle time
2005
In this paper we consider the single machine earliness/tardiness scheduling problem with no idle time. We present two new heuristics, a dispatch rule and a greedy procedure, and also consider the best of the existing dispatch rules. Both dispatch rules use a lookahead parameter that had previously been set at a fixed value. We develop functions that map some instance statistics into appropriate values for that parameter. We also consider the use of dominance rules to improve the solutions obtained by the heuristics. The computational results show that the function-based versions of the heuristics outperform their fixed value counterparts and that the use of the dominance rules can indeed improve solution quality with little additional computational effort.
This research addresses the single machine scheduling problems with controllable processing times. In this area, it is often assumed that the possible processing time of a job can be continuously controlled, i.e. it can be any number in a given interval. When the processing times of jobs are controllable, selected processing times affect both the manufacturing cost and the scheduling performance. In this study, our objective is determining a set of compression/expansion of processing times as well as a sequence of jobs simultaneously, so that total tardiness and earliness on a single machine are minimized. In this way, we first propose a mathematical model for the considered problem and then a net benefit compression-net benefit expansion (NBC-NBE) heuristic is presented for obtaining a set of amounts of compression and expansion of jobs processing times in a given sequence. Also, a simulated annealing approach is used to solve medium to large size problems as an effective local search method. The addressed problem is NP-hard since the single machine total tardiness problem (SMTTP) is already NPhard. The computational results show that our proposed heuristic is an efficient solution method for such Just-In-Time (JIT) problem.
A hybrid algorithm for the single-machine total tardiness problem
Computers & Operations Research, 2009
We propose a hybrid algorithm based on the Ant Colony Optimization (ACO) meta-heuristic, in conjunction with four well-known elimination rules, to tackle the N P -hard single-machine scheduling problem to minimize the total job tardiness. The hybrid algorithm has the same running time as that of ACO. We conducted extensive computational experiments to test the performance of the hybrid algorithm and ACO. The computational results show that the hybrid algorithm can produce optimal or near-optimal solutions quickly, and its performance compares favourably with that of ACO for handling standard instances of the problem.
Heuristic Algorithms for a Job-Shop Problem with Minimizing Total Job Tardiness
In practice, it is often required to process a set of jobs without operation preemptions satisfying temporal and resource constraints. Temporal constraints say that some jobs have to be finished before some others can be started. Resource constraints say that operations processed on the same machine cannot be processed simultaneously. The objective is to construct a schedule specifying when each operation starts such that both temporal and resource constraints are satisfied and the given objective function has a minimum value. One can model such a scheduling process via the following job-shop problem.
Hybrid heuristic algorithms for single machine total weighted tardiness scheduling problems
International Journal of Intelligent Systems Technologies and Applications, 2008
This paper addresses on solving a well known Non Polynomial (NP) hard type problem, namely the single machine total weighted-tardiness problem. The performances of three hybrid heuristic algorithms to solve the single machine scheduling problems with the objective of minimising the total weighted tardiness are presented and compared. In the first hybrid algorithm, a dynamic dispatching rule, namely Modified Due Date (MDD), is hybridised with local search mechanism. In the second hybrid algorithm, a greedy heuristic, namely backward phase, is proposed and hybridised with local search mechanisms. The third hybrid algorithm hybridises the backward phase heuristics with an iterated local search (ILS) having an evolutionary perturbation tool. The algorithms are tested by solving all the 125 benchmark problem instances available in the OR-Library for different sizes and compared with the best known values. It is observed that the hybrid algorithm with evolutionary perturbation tool is performing better than the others.
European Journal of Operational Research, 1996
We consider the dynamic single-machine scheduling problem where the objective is to minimize the sum of weighted earliness and weighted tardiness costs. A single pass heuristic, based on decision theory, is developed for constructing schedules. The heuristic permits schedules with idle time between jobs and behaves like a dispatching procedure. The performance of the new heuristic is examined using 116 published problems for which the optimum solution is known. Its performance is also investigated using 540 randomly generated problems covering a variety of conditions by comparing it to two well known dispatching procedures, adapted for dynamic early/tardy problems. The results indicate that the heuristic performs very well.