A genetic algorithm for job sequencing problems with distinct due dates and general early-tardy penalty weights

Lee, C. Y.; Choi, Joonsung

doi:10.1016/0305-0548(94)00073-h

Cited by 96 publications

(43 citation statements)

References 8 publications

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“…Both Kanet and Sridharan (1991) and Lee and Choi (1995) developed genetic-based algorithms for E=T problems. Kanet and Sridharan investigated the problem of n jobs with nonidentical ready times and sequence-dependent setup times to be scheduled on m uniform machines, with the convex objective function n j=1 j E j + j T j + j SU j ; where SU j represents setup time for job j.…”

Section: Literature On Problems With a Nonregularmentioning

confidence: 99%

“…It is di cult to assess the quality of their procedure because they made no comparisons to optimum solutions. Lee and Choi (1995) presented a search procedure for 1| | j E j + j T j problems to generate near-optimum sequences using crossover and mutation operators and linear scaling of the ÿtness function. They used an embedded timetabling procedure to determine the optimum starting times of jobs in a sequence by inserting idle times when necessary.…”

Section: Literature On Problems With a Nonregularmentioning

confidence: 99%

“…The issue of ÿnding best ways for timetabling a given job sequence has attracted the attention of a number of researchers. Starting with Sidney in 1977, timetabling procedures have been proposed by Lakshminarayan et al (1978), Garey et al (1988), Davis and Kanet (1993), Lee and Choi (1995), and Szwarc and Mukhopadhyay (1995). Fry et al (1984) developed linear programming formulation to timetable jobs.…”

Section: Literature On Problems With a Nonregularmentioning

confidence: 99%

“…These areas Fry, Armstrong, and Blackstone (1984);Fry, Darby-Dowman, and Armstrong (1986);Fry, Leong, and Rakes (1987);Fry, Armstrong, and Rosen (1990); Yano and Kim (1991); Lee and Choi (1995); Szwarc and Mukhopadhyay (1995) Keyser and Sarper (1991); Sridharan and Zhou (1996b) Group 7 (m|rj|non-reg) J |rj| j Ej + j Tj Faaland andSchmitt (1987, 1993) Q|rj; setups| j Ej + j Tj Kanet and Sridharan (1991);Balakrishnan, Kanet, and Sridharan (1997) can be organized according to the following interrelated categories: 1. Further development of algorithms and dominance properties.…”

Section: Research Opportunitiesmentioning

confidence: 99%

“…For a review of these methods see Morton and Pentico (1993). Other approaches that appear promising include application of genetic algorithms (see Sridharan 1991 andLee andChoi 1995), application of basic decision theory (see Chryssolouris et al 1988, Kanet and Zhou 1993, Sridharan and Zhou 1996aand 1996b, and application of neural networks (see Johnston and Adorf 1992). All these methods distinguish themselves from simple forward simulations in that they may include a (limited) capability for backtracking and=or the feature of dynamically changing the search path.…”

Section: Integration Of Timetabling Into Search Proceduresmentioning

confidence: 99%

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Scheduling with Inserted Idle Time: Problem Taxonomy and Literature Review

Kanet

Sridharan

2000

Operations Research

127

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In the context of production scheduling, inserted idle time (IIT) occurs whenever a resource is deliberately kept idle in the face of waiting jobs. IIT schedules are particularly relevant in multimachine industrial situations where earliness costs and=or dynamically arriving jobs with due dates come into play. We provide a taxonomy of environments in which IIT scheduling is relevant, review the extant literature on IIT scheduling, and identify areas of opportunity for future research.

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Section: Literature On Problems With a Nonregularmentioning

confidence: 99%

Section: Literature On Problems With a Nonregularmentioning

confidence: 99%

Section: Literature On Problems With a Nonregularmentioning

confidence: 99%

Section: Research Opportunitiesmentioning

confidence: 99%

Section: Integration Of Timetabling Into Search Proceduresmentioning

confidence: 99%

See 3 more Smart Citations

Scheduling with Inserted Idle Time: Problem Taxonomy and Literature Review

Kanet

Sridharan

2000

Operations Research

127

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Timing problems and algorithms: Time decisions for sequences of activities

Vidal

Crainic²,

Gendreau

et al. 2015

Networks

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Timing problems involve the choice of task execution dates within a predetermined processing sequence, and under various additional constraints or objectives such as time windows, time-dependent costs, or flexible processing times, among others. Their efficient resolution is critical in branch and bound and neighborhood search methods for vehicle routing, project and machine scheduling, as well as in various applications in network optimization, resource allocation, and statistical inference. Timing-related problems have been studied for years, yet research on this subject suffers from a lack of consensus, and most knowledge is scattered among operations research and applied mathematics domains. This article introduces a classification of timing problems and features, as well as a unifying multidisciplinary analysis of timing algorithms. In relation to frequent application cases within branching schemes or neighborhood searches, the efficient resolution of series of similar timing subproblems is also analyzed. A dedicated formalism of reoptimization "by concatenation" is introduced to that extent. The knowledge developed through this analysis is valuable for modeling and algorithmic design, for a wide range of combinatorial optimization problems with time characteristics, including rich vehicle routing settings and emerging nonregular scheduling applications, among others.

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Self evolution algorithm to minimize earliness and tardiness penalties with a common due date on a single machine

Weng

Fujimura

2008

IEEJ Transactions Elec Engng

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Earliness and tardiness penalties are designed for such scheduling problems where the popular Just‐In‐Time (JIT) concept is considered to be of significant importance. In this paper, a self evolution (SE) algorithm is proposed to solve the problem of single‐machine total earliness and tardiness penalties with a common due date. Up to now, no specific attention has been paid to straddling V‐shaped schedules of such problems, which may be better than pure V‐shaped schedules for the early due date cases; and no specific discussions have been made on the start time setting of the first job in a schedule. Therefore, in this research, efforts have been made on digging out the straddling V‐shaped schedules, improving the efficiency of setting the start time of a schedule, and reducing the execution time. In addition, a new RHRM approach is proposed to create the initial solution for evolution, which helps in achieving the fast contingency of the algorithm. The performance of the proposed algorithm has been tested on 280 benchmark instances ranging from 10 to 1000 jobs from the OR Library, and the results show that the proposed SE algorithm delivers much higher efficiency in finding optimal or near‐optimal solutions with both better results in total penalties and significant execution time reduction. Copyright © 2008 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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A genetic algorithm for job sequencing problems with distinct due dates and general early-tardy penalty weights

Cited by 96 publications

References 8 publications

Scheduling with Inserted Idle Time: Problem Taxonomy and Literature Review

Scheduling with Inserted Idle Time: Problem Taxonomy and Literature Review

Timing problems and algorithms: Time decisions for sequences of activities

Self evolution algorithm to minimize earliness and tardiness penalties with a common due date on a single machine

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