scholarly journals A Grey-Fuzzy Multiobjective Model for Supplier Selection and Production-Distribution Planning Considering Consumer Safety

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Muhammad Saad Memon ◽  
Sonia Irshad Mari ◽  
Faheemullah Shaikh ◽  
Shakeel Ahmed Shaikh

Most of the recent product recall incidents indicate that effective management of suppliers and production-distribution planning may play a vital role in increasing product safety. This study explores the opportunities to increase the product safety by analyzing the performance of suppliers and production-distribution system. More precisely, this research analyzes the impact of suppliers’ performance on overall profit of supply chain and impact of increasing consumer safety on total profit of supply chain. The novelty of this study is the development of integrated supplier selection and production-distribution model considering consumer risk and product safety. The proposed model is a grey multiobjective model which considers imprecise information as grey parameters. Furthermore, a novel grey-weighted ε-constrained (GWECON) method is developed to solve the proposed multiobjective model.

Author(s):  
Konstantinos G. Zografos ◽  
loanna M. Giannouli

Although the development of supply chain management trends has been the subject of substantial research, little attention has been devoted to examining the impact of the emerging supply chain management (SCM) trends on the spatial organization of the supply and distribution system. Specifically, the literature lacks an integrated methodological framework for examining the impact of emerging SCM trends on decision making relative to the spatial organization of logistical networks. This analysis has three purposes—( a) develop a conceptual framework for analyzing how decisions are made on the spatial organization of logistical networks, ( b) test the proposed framework via case studies, and ( c) develop a preliminary set of guidelines on the essential elements in making strategic logistical network design decisions. An interesting finding in implementing the proposed methodological framework, which was further supported by the limited empirical research, is that decision-making requirements vary substantially among the industrial and service sectors. This variance reflects differences in objectives and the extent of integration and collaboration of business entities along the respective supply chains.


2009 ◽  
Vol 48 (14) ◽  
pp. 4043-4069 ◽  
Author(s):  
A.S. Safaei ◽  
S.M. Moattar Husseini ◽  
R. Z.-Farahani ◽  
F. Jolai ◽  
S.H. Ghodsypour

Author(s):  
Ana Luísa Ferreira Andrade Ramos ◽  
José António Vasconcelos Ferreira ◽  
Sara Rego da Costa

In the food retail industry, the agility and responsiveness of the supply chain are crucial because demand is volatile and short lead times are mandatory. The logistics performance is of critical importance to provide a high level of efficiency in operations and a high degree of customer satisfaction. The Handling Unit, or the minimum quantity to send to retail stores (the ship-pack), is a factor of considerable influence on logistics efficiency and costs. In this work, it was developed a simple analytical cost model for a Portuguese food retail two-tier distribution system (distribution centre and store) to support the evaluation of the conversion of the handling unit to half-pallet. The results of the model, considering a pilot study with three scenarios, suggest an economic gain of approximately 75% (comparatively to the current situation) in logistics costs. These quantitative results were decisive to guide decision-makers.


Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1363 ◽  
Author(s):  
Weiping Cheng ◽  
Gang Xu ◽  
Hongji Fang ◽  
Dandan Zhao

This paper describes an infrastructure to detect burst events in a water distribution network, which we illustrate using the Guangzhou water distribution system (WDS). We consider three issues: The feasibility and capability of accurate detection, the layout and design of the monitoring infrastructure, and the burst event detection algorithm. Background noise is identified by analyzing the monitored data. A burst event can be accurately detected only when the impact of the burst can be differentiated from the background noise. We hypothesize that there is a minimum pipe diameter below which accurate burst detection is impossible. We found that data from at least two sensors close to the burst event are required to reduce detection errors.


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