Applying a fuzzy multi-objective model for a production–distribution network design problem by using a novel self-adoptive evolutionary algorithm

Goodarzian, Fariba; Hosseini-Nasab, Hasan

doi:10.1080/23302674.2019.1607621

Cited by 37 publications

(16 citation statements)

References 41 publications

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“…It has been proven that the sustainable MSCN problem is NP-hard [22][23][24][25][26][27]. Hence, the literature has seen several metaheuristics that were ordered to solve these NP-hard problems [28][29][30].…”

Section: Solution Methodologymentioning

confidence: 99%

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A Multi-objective Sustainable Medicine Supply Chain Network Design Using a Novel Hybrid Multi-objective Metaheuristic Algorithm

Goodarzian

Hosseini-Nasab

Fakhrzad

2020

IJE

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End-of-life products have a severe impact on the ecological system. Potential production policies and distribution strategies for the newly manufactured product have attracted significant attention to sustainable development. Sustainability in supply chain management has much importance to achieve eco-friendly goals. In this study, we have developed sustainable objectives in the supply chain optimization framework with different constraints. The trade-off between economic, environmental and social effects objectives have identified by ensuring the optimal allocation of different products among various levels. In this regard, a new sustainability multi-objective mixed-integer linear programming mathematical model in the medicine supply chain network is developed. Although the proposed model is an NP-hard problem, we develop a novel hybrid Particle Swarm Optimization and Genetic Algorithm to achieve Pareto solutions. Then, to adjust the important parameters of the algorithms and chose the optimum levels of the significant factors for more efficiency is employed the Taguchi method. The results show that the economic and environmental effects tend to be decreased and the social impacts tend to be increased in the medicine supply chain network which can exhibit the best sustainability performance. The various outcomes of numerical experiments indicate that the proposed solution algorithm is more reliable than other algorithms. The solution methods are complemented with several sensitivity analyses on the input parameters of the model.

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Section: Solution Methodologymentioning

confidence: 99%

“…Hence, we utilize two multi-objective meta-heuristic algorithms (PSO and GA). For more information about these algorithms refer to literature [25][26][27][28][29][30], respectively. Besides, our contribution in this paper, we developed a novel HPSOGA algorithm to solve the presented model.…”

Section: Solution Methodologymentioning

confidence: 99%

A Multi-objective Sustainable Medicine Supply Chain Network Design Using a Novel Hybrid Multi-objective Metaheuristic Algorithm

Goodarzian

Hosseini-Nasab

Fakhrzad

2020

IJE

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“…e multiobjective optimisation mainly includes goals related to maximising products' quality level [10], minimising the average tardiness, and minimising delivery [11]. Owing to the difficulties of collecting data and knowledge about production and distribution planning problems, some works examined real-life case studies such as automotive manufacturing [11], apparel industry [12], pharmaceutical industry [13], and plastic industry [14]. Many researches suppose the availability of deterministic data when developing a production-distribution planning model.…”

Section: Related Literaturementioning

confidence: 99%

“…e limit of backorder's rate is illustrated in constraint (12). Equation (13) limits the production amounts to the random production capacity in regular time under the scenario s. e limitation of production capacity in overtime is written in equation (14). Constraint (15) limits the product inventory levels of production plants to their related inventory storage capacities.…”

Section: Iptmentioning

confidence: 99%

An Integrated Production-Distribution Planning Problem under Demand and Production Capacity Uncertainties: New Formulation and Case Study

Abid

Ayadi

Masmoudi

2020

Mathematical Problems in Engineering

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In this study, we propose to solve a biobjective tactical integrated production-distribution planning problem for a multisite, multiperiod, multiproduct, sea-air intermodal supply chain network under uncertainties. Two random parameters are considered simultaneously: product replenishment orders and production capacity, which are modelled via a finite set of scenarios, using a two-stage stochastic approach. A corresponding mathematical model is developed, coded, and solved using the LINGO 18.0 software optimisation tool. This model aims to simultaneously minimise the total costs of production in both regular and overtime, inventory, distribution, and backordering activities and maximise the customer satisfaction level over the tactical planning horizon. The AUGMECON technique is applied to handle with the multiobjective optimisation. The applicability and the performance of the proposed model are tested through a real-life case study inspired from a medium-sized Tunisian textile and apparel company. Sensitivity analysis on stochastic parameters and managerial insights for the studied supply chain network are argued based on the empirical findings.

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“…Sustainable supply chain means creating a coordinated supply chain by integrating economic, environmental and social considerations with the business systems within a supply chain. This integration is for the efficient and effective management of materials, information and flows related to the purchase, production and distribution of products or services, and its purpose is to meet the needs of stakeholders, increase profits, create competitive advantage and chain sustainability in the short and long term [8]. These types of chains seek to balance economic, environmental, and social objective function.…”

Section: Introductionmentioning

confidence: 99%

Designing a Sustainable Reverse Logistics Network Considering the Conditional Value at Risk and Uncertainty of Demand under Different Quality and Market Scenarios

Sajedi

Sarfaraz

Bamdad

et al. 2020

IJE

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Applying a fuzzy multi-objective model for a production–distribution network design problem by using a novel self-adoptive evolutionary algorithm

Cited by 37 publications

References 41 publications

A Multi-objective Sustainable Medicine Supply Chain Network Design Using a Novel Hybrid Multi-objective Metaheuristic Algorithm

A Multi-objective Sustainable Medicine Supply Chain Network Design Using a Novel Hybrid Multi-objective Metaheuristic Algorithm

An Integrated Production-Distribution Planning Problem under Demand and Production Capacity Uncertainties: New Formulation and Case Study

Designing a Sustainable Reverse Logistics Network Considering the Conditional Value at Risk and Uncertainty of Demand under Different Quality and Market Scenarios

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