Scheduling identical parallel machines with fixed delivery dates to minimize total tardiness

Mensendiek, Arne; Gupta, Jatinder N. D.; Herrmann, J. Berenike

doi:10.1016/j.ejor.2014.12.002

Cited by 34 publications

(14 citation statements)

References 30 publications

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“…Mensendiek et al [18] regarded IPP scheduling to minimize total tardiness where jobs can only be provided at set delivery dates exogenously provided using the TS algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated Scheduling of Tasks and Preventive Maintenance Periods in a Parallel Machine Environment With Single Robot Server

et al. 2021

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In this study, the objective of minimizing makespan has been considered for a scheduling problem of identical parallel machines with a single server and unavailability constraints. The unavailability constraints correspond to preventive maintenance periods. In this study, the jobs and the maintenance periods are scheduled simultaneously. This scheduling problem has a wide range of potential application areas in the manufacturing environment. In addition, the studied problem is a challenging one from theoretical point of view, due to its NP-Hardness. To conduct the study, a lower bound (LB) for the problem, and three metaheuristics namely Simulated Annealing (SA), Tabu Search (TS), and Genetic Algorithm (GA) have been proposed. The best parameters settings of the proposed algorithms were conducted using pilot runs with a Taguchi design. The algorithms performance has been assessed by using a set of test problems generated randomly. These test problems are based on a literature benchmark. The size of the instances, or number of jobs, were up to 500. Along with the performance analysis of the proposed algorithms, the effect of varying processing times and unavailability periods on the performance of the proposed algorithms is studied. The present work provides strong evidence of the efficiency and the performance of the proposed algorithms.

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“…Mensendiek et al [18] regarded IPP scheduling to minimize total tardiness where jobs can only be provided at set delivery dates exogenously provided using the TS algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated Scheduling of Tasks and Preventive Maintenance Periods in a Parallel Machine Environment With Single Robot Server

et al. 2021

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“…Mensendiek et al [57] studied identical PMS problems with a fixed due date which is prevalent in the industry. This problem is solved by two exact and approximate methods, branch and bound and Tabu search and genetic algorithms; respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

A multi objective volleyball premier league algorithm for green scheduling identical parallel machines with splitting jobs

Salimifard

Mohammadi

et al. 2020

Appl Intell

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Parallel machine scheduling is one of the most common studied problems in recent years, however, this classic optimization problem has to achieve two conflicting objectives, i.e. minimizing the total tardiness and minimizing the total wastes, if the scheduling is done in the context of plastic injection industry where jobs are splitting and molds are important constraints. This paper proposes a mathematical model for scheduling parallel machines with splitting jobs and resource constraints. Two minimization objectives - the total tardiness and the number of waste - are considered, simultaneously. The obtained model is a bi-objective integer linear programming model that is shown to be of NP-hard class optimization problems. In this paper, a novel Multi-Objective Volleyball Premier League (MOVPL) algorithm is presented for solving the aforementioned problem. This algorithm uses the crowding distance concept used in NSGA-II as an extension of the Volleyball Premier League (VPL) that we recently introduced. Furthermore, the results are compared with six multi-objective metaheuristic algorithms of MOPSO, NSGA-II, MOGWO, MOALO, MOEA/D, and SPEA2. Using five standard metrics and ten test problems, the performance of the Pareto-based algorithms was investigated. The results demonstrate that in general, the proposed algorithm has supremacy than the other four algorithms.

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“…Mensendiek et al [23] addressed the problem of minimizing the total tardiness of a set of jobs to be scheduled on identical parallel machines, where jobs could only be delivered at certain fixed delivery dates. The authors developed and empirically evaluated both the optimal and heuristic solution procedures to solve their problem.…”

Section: The Literature Reviewmentioning

confidence: 99%

Scheduling of periodic services to customers in dispersed locations from heterogeneous multi-agent companies considering uncertainty: A real case study

2019

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The scheduling problem of periodic services from service providers to customers located in different places and need different services. The service centers are also located in different positions, each of which has limited number of teams with the capability of performing one or some services. The goal is to simultaneously minimize 'total service costs' and 'total earliness/tardiness' in providing services to customers. Providing an optimal maintenance schedule is a big challenge in those companies with dispersed supply centers. In this paper, a novel bi-objective mixed integer linear programming model along with augmented epsilon constraint method is presented to exactly solve this problem. Then, a biobjective meta-heuristic technique based on genetic algorithm is proposed and its performance in solving large-scale problems is assessed. The uncertain parameters are faced through robust possibilistic programming approach to diminish the risk of decision making. Finally, the performance of the proposed model and solution approaches are evaluated through a real case study in maintenance scheduling of compressed natural gas (CNG) stations equipment in Iran.

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Scheduling identical parallel machines with fixed delivery dates to minimize total tardiness

Cited by 34 publications

References 30 publications

Integrated Scheduling of Tasks and Preventive Maintenance Periods in a Parallel Machine Environment With Single Robot Server

Integrated Scheduling of Tasks and Preventive Maintenance Periods in a Parallel Machine Environment With Single Robot Server

A multi objective volleyball premier league algorithm for green scheduling identical parallel machines with splitting jobs

Scheduling of periodic services to customers in dispersed locations from heterogeneous multi-agent companies considering uncertainty: A real case study

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