Scheduling Coupled-Tasks on a Single Machine

Li, Haibing; Zhao, Hairong

doi:10.1109/scis.2007.367681

Cited by 12 publications

(22 citation statements)

References 9 publications

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“…In the single-machine setting, the interleaving and nesting heuristics of Shapiro (1980) are of importance for developing solution methods. Two Tabu Search (TS) algorithms were proposed by Li and Zhao (2007); Condotta and Shakhlevich (2012), though no detailed comparison was reported. Two notable exact algorithms of B&B (Békési et al, 2014) and dynamic programming (Ahr et al, 2004) were proposed; the latter is for the case of the identical problem.…”

Section: Solution Methodsmentioning

confidence: 99%

“…where Pa = j aj, P b = j bj, and C * max is the optimal makespan. Li and Zhao (2007) proposed the first meta-heuristic, i.e., a Tabu Search (TS) algorithm. In order to use permutation representations for generating neighbourhoods, they applied a greedy heuristic, which builds a non-permutation schedule from a given permutation one.…”

Section: T Ecmentioning

confidence: 99%

“…The instances set includes a total number of 250 instances with 20 to 500 jobs, where the task processing times are in the range of 10 and 100, and the delay durations in the range of 300 and 1,300. Ahr et al (2004); Li and Zhao (2007); Brauner et al (2009);Blazewicz et al (2012) adopted a similar approach, i.e., taking values from a discrete uniform interval. The instances in Sherali and Smith (2005) consist of 8 to 14 jobs, with aj taken from the normal distribution with a mean of 30 time units and a standard deviation of 5 time units, i.e., N (30, 5).…”

Section: Previous Instance Generation Schemesmentioning

confidence: 99%

“…Section 5.2 explains the procedure and the generated instances for the single-machine problem and Section 5.3 discusses those for the flow shop setting. Sherali and Smith (2005) {8, 10, 12, 14} (N (30, 5), N (600, 100), N (120, 30)) 20 Li and Zhao (2007) {50 , 8, 9, 10, 11, 12} (1, [1, 10], 1) {7, 8, 9, 10, 11, 12} (N (30, 5), N (600, 100), N (120, 30)) {7, 8, 9, 10, 11, 12} ([1, 100], "Fitted" delays, [1, 100])…”

Section: Previous Instance Generation Schemesmentioning

confidence: 99%

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Coupled Task Scheduling With Exact Delays: Literature Review and Models

2018

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The coupled task scheduling problem concerns scheduling a set of jobs, each with at least two tasks and there is an exact delay period between two consecutive tasks, on a set of machines to optimize a performance criterion. While research on the problem dates back to the 1980s, interests in the computational complexity of variants of the problem and solution methodologies have been evolving in the past few years. This motivates us to present an up-to-date and comprehensive literature review on the topic. Aiming to provide a complete road map for future research on the coupled task scheduling problem, we discuss all the relevant studies and potential research opportunities. In addition, we propose several sets of benchmark instances for the problem in various settings and provide a detailed evaluation of all the available models with a view to facilitating future research on the solution methods.

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Section: Solution Methodsmentioning

confidence: 99%

Section: T Ecmentioning

confidence: 99%

Section: Previous Instance Generation Schemesmentioning

confidence: 99%

Section: Previous Instance Generation Schemesmentioning

confidence: 99%

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Coupled Task Scheduling With Exact Delays: Literature Review and Models

2018

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“…There are a few solution methods for the general case of the coupled task scheduling problem. Some notable works include the branch-and-bound of Békési et al (2014) and tabu search of Li and Zhao (2007) and Condotta and Shakhlevich (2012), though no detailed comparison was reported. These studies utilised instances with different characteristics and did not make them publicly available, making therefore difficult to conduct a comparison study.…”

Section: Introductionmentioning

confidence: 99%

A simple heuristic for the coupled task scheduling problem

2019

El Sawah, S. (Ed.) MODSIM2019, 23rd International Congress on Modelling and Simulation.

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The coupled task scheduling problem deals with the problem of scheduling a set of jobs to be processed on a single machine. Each job consists of two separated tasks where the second task of a job must be started after the completion of its first task plus a predefined exact delay ti me. We study the coupled task scheduling problem with the objective of minimising the maximum completion time, i.e., the makespan. The problem is known to be strongly NP-hard. We propose a simple heuristic for the problem. The heuristic sets the midpoint of given lower and upper bounds as a makespan and solves a feasibility problem. Upon solving the feasibility problem the upper bound is updated to the midpoint. Otherwise, the lower bound is updated to the midpoint. The algorithm keeps iterating until the bound interval is zero. Computational experiments indicate that the proposed heuristic outperforms the exact solver.

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Multi-objective Genetic Algorithm to Reduce Setup Waste in a Single Machine with Coupled-Tasks Scheduling Problem

Hesran¹,

Ladier²,

Botta‐Genoulaz³

2021

Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems

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This article studies a single-machine scheduling problem involving coupled-tasks and hard due dates. A genetic algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA) II model is proposed to carry out a bi-objective optimization of both holding cost and setup-related waste generation. Results show that the multi-objective genetic algorithm outperforms the previous approaches regarding both computation time and objective functions, showing that a reduction of setups of 36% is possible at the expense of an 11% increase in inventory with acceptable computation times. It also highlights the importance of multi-objective optimization for decision-making in case of conflicting objective functions.

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Scheduling Coupled-Tasks on a Single Machine

Cited by 12 publications

References 9 publications

Coupled Task Scheduling With Exact Delays: Literature Review and Models

Coupled Task Scheduling With Exact Delays: Literature Review and Models

A simple heuristic for the coupled task scheduling problem

Multi-objective Genetic Algorithm to Reduce Setup Waste in a Single Machine with Coupled-Tasks Scheduling Problem

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