Multi-objective invasive weeds optimisation algorithm for solving simultaneous scheduling of machines and multi-mode automated guided vehicles

Nabovati, Hojat; Haleh, Hassan; Vahdani, Behnam

doi:10.1504/ejie.2020.105696

Cited by 7 publications

(2 citation statements)

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“…In this paper, because of a good performance of MOIWO in Nabovati, et al [56], Keramatpour, et al [57], Nabovati, et al [58], this algorithm was selected as an indicator for the efficiency of the MOVDO algorithm.…”

Section: Multi-objective Invasive Weeds Optimization Algorithm (Moiwo)mentioning

confidence: 99%

A multi-objective vibration damping optimization algorithm for solving a cellular manufacturing system with manpower and tool allocation

et al. 2020

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In this paper, a novel bi-objectivemathematical model is proposed to designa fourdimensional (i.e., part, machine, operator, and tool) cellular manufacturing system (CMS) in a dynamic environment. The main objectives of this model are to 1) minimize total costs including tools processing cost, costs of transporting cells between various cells, machine setup cost, and operators' educational costs, and 2) maximizing skill level of operators. The developed model is strictly NP-hard and exact algorithms cannot find globally optimal solutions in reasonably computational time. So, a multi-objective vibration damping optimization algorithm (MOVDO) with a new solution structure that satisfies all the constraints and generates feasible solutions is proposed to find near-optimal solutions in reasonablycomputational time. Since there is no benchmark available in the literature, three other meta-heuristic algorithms (i.e., non-dominated sorting genetic algorithm (NSGA-II), multi-objective particle swarm optimization (MOPSO) and multi-objective invasive weeds optimization (MOIWO)) with the similar solution structure are developed to validate the performance of the proposedMOVDO algorithm for solving various instances of the developed model. The result of comparing theirperformances based on statistical tests and different measuring metrics reveals that the proposed MOVDO algorithm outperforms remarkably better than other meta-heuristics used in this paper.

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Section: Multi-objective Invasive Weeds Optimization Algorithm (Moiwo)mentioning

confidence: 99%

A multi-objective vibration damping optimization algorithm for solving a cellular manufacturing system with manpower and tool allocation

et al. 2020

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“…GFJSP Under Time-of-Use (in this paper) YES YES YES YES Many different approaches have been applied to solve the problem due to the difficult nature of FJSP. Some of the very recent approaches include biogeography-based optimization [31], the firefly algorithm [32], heuristics [33], invasive weed optimization [34], and differential evolution [35]. However, the genetic algorithm (GA) remains the most frequently used algorithm for the FJSP [36] and has proven to be one of the most effective evolutionary techniques for solving FJSPs [37].…”

Section: Introductionmentioning

confidence: 99%

The Green Flexible Job-Shop Scheduling Problem Considering Cost, Carbon Emissions, and Customer Satisfaction under Time-of-Use Electricity Pricing

Jia,

Yang,

et al. 2024

Sustainability

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Exploration of the green flexible job-shop scheduling problem is essential for enterprises aiming for sustainable practices, including energy conservation, emissions reduction, and enhanced economic and social benefits. While existing research has predominantly focused on carbon emissions or energy consumption as green scheduling objectives, this paper addresses the broader scope by incorporating the impact of variable energy prices on energy cost. Through the introduction of an energy cost model based on time-of-use electricity pricing, the study formulates a multi-objective optimization model for green flexible job-shop scheduling. The objectives include minimizing cost, reducing carbon emissions, and maximizing customer satisfaction. To prevent premature convergence and maintain population diversity, an enhanced genetic algorithm is employed for solving. The validation of the algorithm’s effectiveness is demonstrated through specific examples, providing decision results for optimal scheduling under various weight combinations. The research outcomes hold substantial practical value as they can significantly reduce energy expenses, lower carbon emissions, and elevate customer satisfaction while safeguarding production efficiency. This contributes to enhancing the market competitiveness and green brand image of businesses.

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An integrated scheduling approach considering dispatching strategy and conflict-free route of AMRs in flexible job shop

Liu

Sun

et al. 2022

Int J Adv Manuf Technol

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Multi-objective invasive weeds optimisation algorithm for solving simultaneous scheduling of machines and multi-mode automated guided vehicles

Cited by 7 publications

References 0 publications

A multi-objective vibration damping optimization algorithm for solving a cellular manufacturing system with manpower and tool allocation

A multi-objective vibration damping optimization algorithm for solving a cellular manufacturing system with manpower and tool allocation

The Green Flexible Job-Shop Scheduling Problem Considering Cost, Carbon Emissions, and Customer Satisfaction under Time-of-Use Electricity Pricing

An integrated scheduling approach considering dispatching strategy and conflict-free route of AMRs in flexible job shop

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