Integrated circuit (IC) pricing

Webb, G. Kent

doi:10.1016/1047-8310(94)90005-1

Cited by 21 publications

(9 citation statements)

References 8 publications

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“…However, in most cases, it is not able to be solved in polynomial time (Gonzalez and Sahni, 1978), which leads to the study on approximation algorithms (Garey and Johnson, 1979;Smutnicki, 1998). Many real applications have supported Wright's theory (1936) where the processing time can be remarkably reduced with the increase of production requirements (Webb, 1994). Biskup (1999) and Cheng and Wang (2000) successfully introduced Wright's theory in scheduling.…”

Section: Literature Reviewmentioning

confidence: 99%

Minimization of total energy consumption in an m-machine flow shop with an exponential time-dependent learning effect

Liu¹,

Shi²,

Shi³

2018

Front. Eng

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This study investigates an energy-aware flow shop scheduling problem with a time-dependent learning effect. The relationship between the traditional and the proposed scheduling problem is shown and objective is to determine a job sequence in which the total energy consumption is minimized. To provide an efficient solution framework, composite lower bounds are proposed to be used in a solution approach with the name of Boundsbased Nested Partition (BBNP). A worst-case analysis on shortest process time heuristic is conducted for theoretical measurement. Computational experiments are performed on randomly generated test instances to evaluate the proposed algorithms. Results show that BBNP has better performance than conventional heuristics and provides considerable computational advantage.

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Section: Literature Reviewmentioning

confidence: 99%

Minimization of total energy consumption in an m-machine flow shop with an exponential time-dependent learning effect

Liu¹,

Shi²,

Shi³

2018

Front. Eng

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“…This learning effect has a large impact on mass production. For example, it was reported that, in the semiconductor industry, the efficiency gains cause the price to drop by 10-30% [2]. Recently, new proof of the impact of learning effects from a new car-assembly plant was presented in [3].…”

Section: Introductionmentioning

confidence: 99%

“…, }, are available for processing at time zero and are to be processed on a single machine. A schedule is defined by a job sequence = ( [1], [2], . .…”

Section: Introductionmentioning

confidence: 99%

Scheduling with Learning Effects and/or Time-Dependent Processing Times to Minimize the Weighted Number of Tardy Jobs on a Single Machine

Qian

Steiner

2013

Mathematical Problems in Engineering

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We consider single machine scheduling problems with learning/deterioration effects and time-dependent processing times, with due date assignment consideration, and our objective is to minimize the weighted number of tardy jobs. By reducing all versions of the problem to an assignment problem, we solve them inO(n4) time. For some important special cases, the time complexity can be improved to beO(n2) using dynamic programming techniques.

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“…The benefits following the theory of the learning effect were soon recognized by USA War Production Board and the methodology proposed by Wright was used to plan the production of airplanes for the World War II needs (see Roberts 1983). Further empirical studies on the learning effect carried out within the last 60 years horizon proved its significant impact on productivity in manufacturing systems specialized in Hi-Tech electronic equipment (Adler and Clark 1991), memory chips and circuit boards (Webb 1994), electronic guidance systems (Kerzner 1998) and in many others (e.g. Carlson and Rowe 1976;Cochran 1960;Holzer and Riahi-Belkaoui 1986;Jaber and Bonney 1999;Lien and Rasch 2001;Yelle 1979).…”

Section: Introductionmentioning

confidence: 99%

“…Thus, it allows to improve lot-sizes, worker management, energy/resource consumption, etc. (e.g., Keachie and Fontana 1966;Kerzner 1998;Li and Cheng 1994;Webb 1994). Nevertheless, it is not possible to optimize time and/or cost objectives beyond reductions resulting from learning-by-doing (Biskup 2008).…”

Section: Introductionmentioning

confidence: 99%

Scheduling problems with position dependent job processing times: computational complexity results

Rudek

2012

Ann Oper Res

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In this paper, we analyse single machine scheduling problems with learning and aging effects to minimize one of the following objectives: the makespan with release dates, the maximum lateness and the number of late jobs. The phenomena of learning and aging are modeled by job processing times described by non-increasing (learning) or non-decreasing (aging) functions dependent on the number of previously processed jobs, i.e., a job position in a sequence. We prove that the considered problems are strongly NP-hard even if job processing times are described by simple linear functions dependent on a number of processed jobs. Additionally, we show a property of equivalence between problems with learning and aging models. We also prove that if the function describing decrease/increase of a job processing time is the same for each job then the problems with the considered objectives are polynomially solvable even if the function is arbitrary. Therefore, we determine the boundary between polynomially solvable and strongly NP-hard cases.

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Integrated circuit (IC) pricing

Cited by 21 publications

References 8 publications

Minimization of total energy consumption in an m-machine flow shop with an exponential time-dependent learning effect

Minimization of total energy consumption in an m-machine flow shop with an exponential time-dependent learning effect

Scheduling with Learning Effects and/or Time-Dependent Processing Times to Minimize the Weighted Number of Tardy Jobs on a Single Machine

Scheduling problems with position dependent job processing times: computational complexity results

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