Capacitated production planning by parallel genetic algorithm for a multi-echelon and multi-site TFT-LCD panel manufacturing supply chain

Wang, Kung-Min; Wang, Kung‐Jeng; Chen, Chou-Cheng

doi:10.1016/j.asoc.2022.109371

Cited by 6 publications

(2 citation statements)

References 30 publications

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“…Although WOA and VNS have a good convergence speed at the early 10% NFEs, then, they often trap into local optima points. To compare the proposed algorithm with the existing techniques for SCM, a population-based metaheuristic based on genetic algorithm (GA) [44], a solution-based metaheuristic based on simulated annealing (SA) [45], and a combined metaheuristic based on GA and SA (GLGASA) [38] have been also used for the PFSCM optimization considering our Case Study dataset. The OF obtained by the different techniques are provided in Table 16.…”

Section: Validation Of H-woa-vns Against the Exact Methodsmentioning

confidence: 99%

Designing a Renewable and Sustainable Phosphorus Fertilizer Supply Chain Network using an Ensemble Knowledge-based Heuristic-Metaheuristic Algorithm

Shokouhifar¹,

Sohrabi²,

Rabbani³

et al. 2022

Preprint

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Phosphorus (P) is the most important substance in inorganic fertilizers used in agriculture industry. In this study, a multi-product and multi-objective model is presented considering economic and environmental concerns to design a renewable and sustainable P-fertilizer supply chain management (PFSCM). To handle complexities of the proposed model, an ensemble knowledge-based three-stage heuristic-metaheuristic algorithm utilizing heuristic information available in the model, whale optimization algorithm, and variable neighborhood search (named H-WOA-VNS) is proposed. At first, a problem-dependent heuristic is designed to generate a set of near-optimal feasible solutions. These solutions are fed into a population-based whale optimization algorithm which benefits from both exploration and exploitation strategies. Finally, a single-solution metaheuristic based on variable neighborhood search is applied to further improve the quality of the solution using local search operators. The objective function of the algorithm is formulated as a weighted average function to minimize total economic cost, while increasing crop yield and P use efficiency. Experimental results over five synthetic datasets and a real case study of the P-fertilizer supply chain confirm the superiority of the proposed method against the state-of-the-art techniques. The results demonstrate that the proposed method performs well in optimizing both the economic cost and environmental issues.

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Section: Validation Of H-woa-vns Against the Exact Methodsmentioning

confidence: 99%

Designing a Renewable and Sustainable Phosphorus Fertilizer Supply Chain Network using an Ensemble Knowledge-based Heuristic-Metaheuristic Algorithm

Shokouhifar¹,

Sohrabi²,

Rabbani³

et al. 2022

Preprint

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“…This study, which investigates a single vendor-multiple buyer supply chain system with reactive lateral transhipment, will result in a complex optimisation model. Softcomputing models, such as genetic algorithm (GA) and simulated annealing, can be used to solve problems with a high level of complexity [29]. Gholizadeh and Fazlollahtabar [30] have used a modified GA to solve a closed-loop supply chain system.…”

Section: Introductionmentioning

confidence: 99%

Optimisation-in-the-loop simulation of multi products single vendor-multi buyers supply chain systems with reactive lateral transhipment

Purnomo

2023

j. sist. manaj. ind.

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Considering that batik is one of the most popular products in Indonesia, it is important to analyse the supply chain system for batik products. In reality, the supply chain system for batik products enables orders between buyers to receive products more rapidly, allowing them to anticipate stock outs and obtain lower ordering costs than when ordering from vendors. It is referred to as reactive lateral transshipment. This paper discusses the development of a simulation-based stochastic optimisation model for a batik product supply chain system with multiproducts and single vendor-multi buyers. The utilised solution searching algorithm is a modified Genetic Algorithms (GA) executed in-loop with the developed simulation-based stochastic model. The results demonstrate that the proposed modified GA is able to provide a global optimum solution, allowing the proposed simulation-based stochastic model to reduce the joint total cost (JTC) of the investigated supply chain system by up to 19% when compared to the local optimisation model in each supply chain party.

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Multi-subpopulation parallel computing genetic algorithm for the semiconductor packaging scheduling problem with auxiliary resource constraints

Wang

Lin

Liang

et al. 2023

Applied Soft Computing

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Capacitated production planning by parallel genetic algorithm for a multi-echelon and multi-site TFT-LCD panel manufacturing supply chain

Cited by 6 publications

References 30 publications

Designing a Renewable and Sustainable Phosphorus Fertilizer Supply Chain Network using an Ensemble Knowledge-based Heuristic-Metaheuristic Algorithm

Designing a Renewable and Sustainable Phosphorus Fertilizer Supply Chain Network using an Ensemble Knowledge-based Heuristic-Metaheuristic Algorithm

Optimisation-in-the-loop simulation of multi products single vendor-multi buyers supply chain systems with reactive lateral transhipment

Multi-subpopulation parallel computing genetic algorithm for the semiconductor packaging scheduling problem with auxiliary resource constraints

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