An Evolutionary Approach for the Design and Scheduling of Electroplating Facilities

Manier, Marié-Ange; Lamrous, Sid

doi:10.1007/s10852-008-9083-z

Cited by 24 publications

(27 citation statements)

References 9 publications

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“…This reduction would be explained by the direct resolution of the problem with a bi-objective algorithm. A Pareto front containing solutions is reached faster than in [28]. The computation time of the initialization phase represents 70 % of this time.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…The average execution time for each instance is 145 min. Compared to [28] with the same material conditions, population sizes and stopping conditions, the execution time is almost halved. This reduction would be explained by the direct resolution of the problem with a bi-objective algorithm.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…Hence, to our best knowledge, the CHDSP with both objectives of minimizing the fleet size and minimizing the cycle time has only and first be tackled by Manier and Lamrous [1] and [28]. In these studies, the fleet size was a variable of the problem.…”

Section: State Of the Artmentioning

confidence: 99%

“…Then, we evaluate each associated solution. The evaluation is done due to the same Mixed Integer Linear Programming Model (MILP) proposed by Manier and Lamrous [28]. If the schedule is feasible (i.e., if all constraints are respected), this evaluation provides the resulting period T for each moving sequence S h decoded from the list L. Hence, for each generated list L, we get the triplet (H, S h , T ).…”

Section: B the Scheduling Dimensionmentioning

confidence: 99%

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Genetic Algorithm Based Approach for the Multi-Hoist Design and Scheduling Problem

Laajili

Sid

Marie-Ange

et al. 2019

2019 International Conference on Industrial Engineering and Systems Management (IESM)

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Electroplating facilities often face the Cyclic Hoist Scheduling Problem when a repetitive sequence of moves is searched for the hoists. This paper addresses this optimization problem extended to the design of the workshop, where we aim to minimize both the cycle time and the number of hoists used. For this goal, we propose a genetic meta-heuristic approach which introduces a novel solution encoding to enlarge the solutions' search space. Our encoding procedure is based on hoists' empty moves, and includes separator characters. With the latter, we obtain solutions that were not reachable by previous approaches. Each solution obtained thanks to the genetic operators is evaluated by using a Mixed Integer Linear Program. This one checks the constraints of the problem (such as capacity constraints and soaking time bounds) and computes the smallest cycle time for a given moving sequence and its associated number of hoists. Some results are presented using benchmark instances for which our approach allows to improve the best known solutions.

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Section: Experiments and Resultsmentioning

confidence: 99%

Section: Experiments and Resultsmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Section: B the Scheduling Dimensionmentioning

confidence: 99%

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Genetic Algorithm Based Approach for the Multi-Hoist Design and Scheduling Problem

Laajili

Sid

Marie-Ange

et al. 2019

2019 International Conference on Industrial Engineering and Systems Management (IESM)

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“…Manier et al [15] first formulated a mathematical model with disjunctive constraints and then proposed a branch-andbound like algorithm for finding the optimal schedules for multiple robots. Manier and Lamrous [16] proposed an evolutionary approach to minimize the number of robots on parallel tracks. Moreover, Che and Chu [17] and Leung et al [18] presented a specific B&B algorithm and an MIP approach for the multiple robots scheduling problem with unidirectional part flow, where the part processing route is the same as the machine arrange sequence.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Quantum Evolutionary Algorithm with Improved Decoding Scheme for a Robotic Flow Shop Scheduling Problem

Lei¹,

Manier²,

Manier³

et al. 2017

Mathematical Problems in Engineering

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We aim at solving the cyclic scheduling problem with a single robot and flexible processing times in a robotic flow shop, which is a well-known optimization problem in advanced manufacturing systems. The objective of the problem is to find an optimal robot move sequence such that the throughput rate is maximized. We propose a hybrid algorithm based on the Quantum-Inspired Evolutionary Algorithm (QEA) and genetic operators for solving the problem. The algorithm integrates three different decoding strategies to convert quantum individuals into robot move sequences. The Q-gate is applied to update the states of Q-bits in each individual. Besides, crossover and mutation operators with adaptive probabilities are used to increase the population diversity. A repairing procedure is proposed to deal with infeasible individuals. Comparison results on both benchmark and randomly generated instances demonstrate that the proposed algorithm is more effective in solving the studied problem in terms of solution quality and computational time.

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Hoist Scheduling Problem

Bloch¹,

Manier²,

Baptiste³

et al. 2008

Production Scheduling

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An Evolutionary Approach for the Design and Scheduling of Electroplating Facilities

Cited by 24 publications

References 9 publications

Genetic Algorithm Based Approach for the Multi-Hoist Design and Scheduling Problem

Genetic Algorithm Based Approach for the Multi-Hoist Design and Scheduling Problem

A Hybrid Quantum Evolutionary Algorithm with Improved Decoding Scheme for a Robotic Flow Shop Scheduling Problem

Hoist Scheduling Problem

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