1991IIE TransactionsRequires access

Single Machine Tardiness Sequencing Heuristics

Chris N. Potts, Luk N. Van Wassenhove

Open publisher page 200 citations

Abstract

This paper presents a collection of heuristics for the single machine total (weighted) tardiness problem. The methods considered range from simple quick and dirty heuristics to more sophisticated algorithms exploiting problem structure. These heuristics are compared to interchange and simulated annealing methods on a large set of test problems. For the total tardiness problem a heuristic based on decomposition performs very well, whereas for the total weighted tardiness problem simulated annealing appears to be a viable approach. Our computational results also indicate that straightforward interchange methods perform remarkably well.

About this research paper

What this paper is about

This paper presents a collection of heuristics for the single machine total (weighted) tardiness problem. The methods considered range from simple quick and dirty heuristics to more sophisticated algorithms exploiting problem structure. These heuristics are compared to interchange and simulated annealing methods on a large set of test problems. For the total tardiness problem a heuristic based on decomposition performs very well, whereas for the total weighted tardiness problem simulated annealing appears to be a viable approach. Our computational results also indicate that straightforward interchange methods perform remarkably well.

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OpenAlex reports 200 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper presents a collection of heuristics for the single machine total (weighted) tardiness problem. The methods considered range from simple quick and dirty heuristics to more sophisticated algorithms exploiting problem structure. These heuristics are compared to interchange and simulated annealing methods on a large set of test problems. For the total tardiness problem a heuristic based on decomposition performs very well, whereas for the total weighted tardiness problem simulated annealing appears to be a viable approach. Our computational results also indicate that straightforward interchange methods perform remarkably well.

Key concepts: Tardiness, Heuristics, Simulated annealing, Mathematical optimization, Computer science, Heuristic, Range (aeronautics), Algorithm

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