Local search with controlled deterioration for multi-objective scheduling in dual-resource constrained flexible job shop

Lei, Deming; Tan, Xianfeng

doi:10.1109/ccdc.2016.7531874

Cited by 6 publications

(6 citation statements)

References 13 publications

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“…where PI represents the sum of the pose index; MMHI represents the manual material handling index; FI represents the action strength index; EP represents other unconsidered risk points. According to Equation ( 9), the ergonomic risk of worker c when operating different machine can be obtained, the total risk value R d of each worker is calculated by Equation (10), and the maximum ergonomic risk of all workers is calculated by Equation (11).…”

Section: Formulations Of Sfjspcdrmentioning

confidence: 99%

“…The makespan is calculated with Equation (1), and the total energy consumption E of all machines is calculated with Equation ( 2). The maximum ergonomic risk of all workers R max is calculated u Equation (11). Equation (13) indicates that the next operation of one job can start only after the immediately precedent operation has been finished.…”

Section: Formulations Of Sfjspcdrmentioning

confidence: 99%

“…For example, Lei et al [10] proposed a new decoding method for the dual resource scheduling problem. In their subsequent research [11], based on this decoding method, the algorithm was improved with the simulated annealing to obtain a better solution; Li et al [12] employed a branch population genetic algorithm; Gao et al [13] employed the shuffled multi-swarm micro-migrating birds optimisation (SM 2 -MBO) algorithm; Zheng et al [14] employed a knowledge-guided fruit fly optimisation algorithm; Yazdani et al [15] employed the evolutionary algorithm; and Wu et al [16] employed the NSGA-II algorithm to explore the dual resource scheduling problem.…”

Section: Introductionmentioning

confidence: 99%

“…[10] proposed a new decoding method for the dual resource scheduling problem. In their subsequent research [11], based on this decoding method, the algorithm was improved with the simulated annealing to obtain a better solution; Li et al. [12] employed a branch population genetic algorithm; Gao et al.…”

Section: Introductionmentioning

confidence: 99%

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A survival duration‐guided NSGA‐III for sustainable flexible job shop scheduling problem considering dual resources

2021

IET Collab Intel Manufact

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Considering the increasing concern on sustainable development from manufacturers, focus is given to three kinds of indicators of sustainable development, that is, economy, environment, and society, and schedule two types of resource, that is machines and workers, simultaneously in the classical flexible job shop scheduling problem. The authors define it as a sustainable flexible job shop scheduling problem considering dual resources (SFJSPCDR). First, a model of the SFJSPCDR is formulated to optimise the makespan, the energy consumption, and the ergonomic risk simultaneously. Second, an improved survival duration-guided NSGA-III algorithm (SDG-NSGA-III) is proposed to solve SFJSPCDR. The survival duration of each individual determines whether it takes part in generating offspring. In order to balance the energy consumption and ergonomic risk while minimising the makespan, a double-low decoding algorithm is proposed, which is composed of two decoding algorithms. Cross-generation selection is employed with the non-dominated sorting, and the next-generation population is selected according to the reference point-based selection strategy. In addition, a restart strategy is also integrated to improve the exploration and exploitation performance of the SDG-NSGA-III algorithm. Finally, a group of experiments are carried out and the results prove the effectiveness of the proposed algorithm. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Formulations Of Sfjspcdrmentioning

confidence: 99%

Section: Formulations Of Sfjspcdrmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A survival duration‐guided NSGA‐III for sustainable flexible job shop scheduling problem considering dual resources

2021

IET Collab Intel Manufact

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“…Hamedi et al [14] proposed a Multi-Objective Tabu Search algorithm based on Goal Programming. Lei and Tan [15] proposed a hybrid Genetic Algorithm with Local Search with Controlled Deterioration for the multi-objective DRCFJSP. The algorithm in question performs global search using the Genetic Algorithm and incorporates a local search step using VNS in a similar fashion to previous work of Lei and Guo [11], but also accepting dominated solutions in addition to dominating ones, with a deteriorating factor.…”

Section: Related Workmentioning

confidence: 99%

A New Shopfloor Orchestration Approach for Collaborative Human-Robot Device Disassembly

Chatzikonstantinou

Giakoumis

Tzovaras

2019

2019 IEEE SmartWorld, Ubiquitous Intelligence &Amp; Computing, Advanced &Amp; Trusted Computing, Scalable Computing &Amp; Commu

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We present a new approach to tackle the problem of task assignment and scheduling in human-robot teams that undertake collaborative device disassembly tasks. The proposed approach is a hybrid between a global search metaheuristic and an adaptive greedy operation assignment and scheduling algorithm. We propose the concept of an Adaptive (work)Cell, (aCell), which becomes the basis for the hierarchical organization of the proposed search approach. At high level, metaheuristic search establishes resource constraints for each aCell and determines parameters for the task-level operation scheduling. At low level, the task-level scheduling algorithm produces feasible assignments and schedules within a single aCell by backtracking through feasible time slots using an adaptive score metric. The advantage of the proposed approach is that it clearly delineates between higher level state space exploration and focused, taskoriented exploitation. We validate the proposed approach on a class of novel multi-objective benchmark problems involving human-robot teams collaborating throughout a factory floor, addressing specifically for the first time the problem of device disassembly tasks, relevant to WEEE recycling, with additional constraints, where we obtain favorable results.

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A worker constrained flexible job shop scheduling problem with sequence-dependent setup times

2018

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Local search with controlled deterioration for multi-objective scheduling in dual-resource constrained flexible job shop

Cited by 6 publications

References 13 publications

A survival duration‐guided NSGA‐III for sustainable flexible job shop scheduling problem considering dual resources

A survival duration‐guided NSGA‐III for sustainable flexible job shop scheduling problem considering dual resources

A New Shopfloor Orchestration Approach for Collaborative Human-Robot Device Disassembly

A worker constrained flexible job shop scheduling problem with sequence-dependent setup times

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