Minimizing total tardiness and earliness on unrelated parallel machines with controllable processing times

Kayvanfar, Vahid; Komaki, G.M.; Aalaei, Amin; Zandieh, M.

doi:10.1016/j.cor.2013.08.003

Cited by 46 publications

(20 citation statements)

References 48 publications

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“…Kayvanfar, Mahdavi, and Komaki (2013) presented a net benefit compression-net benefit expansion (NBC-NBE) heuristic to optimize processing times for single machine scheduling problems with a given sequence. To solve the unrelated parallel machine scheduling problem (PMSP) with CPT, Kayvanfar, Komaki, Aalaei, and Zandieh (2014) proposed a parallel net benefit compression-net benefit expansion (PNBC-NBE) heuristic for optimizing the job processing times, and some evolutional algorithms for optimizing the job sequence on each machine.…”

Section: Scheduling Problems Involving Cptmentioning

confidence: 99%

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

Jiang

Liu

Hao

et al. 2015

Computers & Industrial Engineering

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Section: Scheduling Problems Involving Cptmentioning

confidence: 99%

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

Jiang

Liu

Hao

et al. 2015

Computers & Industrial Engineering

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“…He proposes heuristic procedures and tests their performance via a simulation model. Kayvanfar et al (2014) proposes heuristic algorithms to solve a scheduling problem on unrelated parallel machines where processing time compression/expansion costs and total earliness and tardiness objectives are under consideration. Mor and Mosheiov (2014) deal with batch processing of identical jobs where Set-up time is required before each batch.…”

Section: Introductionmentioning

confidence: 99%

Rescheduling with controllable processing times for number of disrupted jobs and manufacturing cost objectives

Gürel

Cincioğlu

2014

International Journal of Production Research

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We consider a machine rescheduling problem that arises when a disruption such as machine breakdown occurs to a given schedule. Machine unavailability due to a breakdown requires repairing the schedule as the original schedule becomes infeasible. When repairing a disrupted schedule a desirable goal is to complete each disrupted job on time, i.e. not later than the planned completion time in the original schedule. We consider the case where processing times of jobs are controllable and compressing the processing time of a job requires extra processing cost. Usually, there exists a nonlinear relation between the processing time and manufacturing cost. We solve a bicriteria rescheduling problem that trades off the number of on-time jobs and manufacturing cost objectives. We give a mixed-integer second-order cone programming formulation for the problem. We develop a heuristic search algorithm to generate efficient solutions for the problem. Heuristic algorithm searches solution space by moving and swapping jobs among machines. We develop cost change estimates for job moves and swaps so that the heuristic implements only promising moves and hence generates a set of efficient solutions in reasonably short CPU times.

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“…Baker and Scudder [15] published a comprehensive state-of-the-art review for different variants of the / problem including the problem with a CDD. Also, many papers addressed the same objective in multimachine scheduling environment such as parallel machines (e.g., Emmons [16], Cheng and Chen [17], Alvarez-Valdes et al [18], Kayvanfar et al [19], Li et al [20], Kubiak et al [21]) and flow shops (e.g., Sarper [22], Sung and Min [23], Mosheiov [24], Gupta et al [25], Lauff and Werner [26], Chandra et al [27], Behnamian et al [28], and M'Hallah [29]). Much less has been published on scheduling problems for job shops (e.g., Lauff and Werner [30], Baptiste et al [31], Yang et al [32], and Wang and Li [33]).…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Heuristic and Exact Algorithms for the Two-Machine Just in Time Job Shop Scheduling Problem

Al-Salem

Bedoya-Valencia

Rabadi

2016

Mathematical Problems in Engineering

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The problem addressed in this paper is the two-machine job shop scheduling problem when the objective is to minimize the total earliness and tardiness from a common due date (CDD) for a set of jobs when their weights equal 1 (unweighted problem). This objective became very significant after the introduction of the Just in Time manufacturing approach. A procedure to determine whether the CDD is restricted or unrestricted is developed and a semirestricted CDD is defined. Algorithms are introduced to find the optimal solution when the CDD is unrestricted and semirestricted. When the CDD is restricted, which is a much harder problem, a heuristic algorithm is proposed to find approximate solutions. Through computational experiments, the heuristic algorithms' performance is evaluated with problems up to 500 jobs.

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Minimizing total tardiness and earliness on unrelated parallel machines with controllable processing times

Cited by 46 publications

References 48 publications

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

A bi-layer optimization approach for a hybrid flow shop scheduling problem involving controllable processing times in the steelmaking industry

Rescheduling with controllable processing times for number of disrupted jobs and manufacturing cost objectives

Heuristic and Exact Algorithms for the Two-Machine Just in Time Job Shop Scheduling Problem

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