Quality management systems selection using FAHP and mixed integer programming

In current paper, an organized and quantitative approach is proposed for selection of quality management systems. The proposed model of this paper first uses fuzzy analytic hierarchical process to rank different quality management systems. Since there are normally various constraints associated with the selection of quality management, we propose a 0-1 programming for selecting an optimal mix of quality management systems. We also use the proposed model of this paper for a real-world case study of research center in aerial industries and the results are discussed

Investigating Cause and Effect Relationships and Prioritizing of GM Assessment Indexes based on Economic, Resources, Energy and Environmental Attributes and PSR Framework using Gray DEMATAL

Nowadays the role of green manufacturing (GM) in sustainable development is evident and irrefutable therefore organizations seek to introduce themselves green in order to maintain their image toward their community. The usual method of sustainability and greenness assessment of a system is making use of indicators and indexes which are classified into several groups based on their characteristics. An important type of index categorization is based on four sustainability attributes including economic, energy, environment and recourses as well as pressure-state-response model (PSR). Because of the research gap about interactions relationships on indexes and investigating their influence others and influence by others. Since, indexes in each group could be effective on other indexes and be overlapped to some extent, it is necessary to prioritize and evaluate cause and effect relations by use of an appropriate method. We consider the relationship and prioritize most important indexes to evaluate manufacturing' greenness based on aforementioned sustainability attributes and PSR model. Purpose data is gathered by survey GM experts questionnaires, including 41 indexes plus 4 mentioned attributes, totally as 45 factors in 13 groups. In order to data analysis, with respect to the non-certainty and insufficient information, Grey DEMATEL method is used.Atualmente, o papel da manufatura verde (GM, Green Manufacturing) no desenvolvimento sustentável é evidente e irrefutável, portanto, as organizações procuram se apresentar “verdes” para manter sua imagem em sua comunidade. O método usual de avaliação da sustentabilidade e do verdor de um sistema é o uso de indicadores e índices que são classificados em vários grupos com base em suas características. Um tipo importante de categorização de índices é baseado em quatro atributos de sustentabilidade, incluindo econômico, energia, meio ambiente e recursos, além do modelo pressão-resposta-estado (PSR, Pressure-State-Response). Tendo em vista a lacuna de pesquisa sobre as relações de interações em índices faz-se necessário investigar a influência de outros e quais são influenciados por outros. Como os índices em cada grupo podem ser efetivos em outros índices e serem sobrepostos em certa medida, assim é essencial priorizar e avaliar as relações de causa e efeito pelo uso de um método apropriado. Consideramos o relacionamento e priorizamos os índices mais importantes para avaliar o verdor da manufatura com base nos atributos de sustentabilidade e no modelo de PSR. Os dados são coletados por questionários especializados em GM, incluindo 41 índices mais os 4 atributos mencionados, totalizando 45 fatores em 13 grupos. A fim de analisar os dados, no que diz respeito às informações não seguras e insuficientes, é utilizado o método Gray DEMATEL

A Robust Two-Stage Stochastic Location-Routing-Inventory Model for Perishable Items

The aim of this study is to develop a robust two-stage stochastic location-routing-inventory model for perishable items. The proposed model is implemented in a two-stage structure. The first-stage decisions determine the establishment of distribution centres and the second-stage decisions identify the other variables of the problem. In order to reduce the effect of different scenarios on the outputs of the problem, the two-stage model is developed to a robust model. Two variability criteria called \u27Partial Lower Deviation from Mean\u27 (PLDM) and \u27Partial Lower Deviation from Target\u27 (PLDT) are considered for the problem. This robust model can manage the variability of different scenarios considering the variability needed for the problem. The summary of the results of the models indicate that the supply cost, the setup cost, the vehicle supply cost, and the production cost comprise 55%, 28%, 3%, and 14% of the total costs of the supply chain, respectively. Similarly, the ratio of net profit margin to the total revenue of the supply chain derived from the division of the objective function by the revenue function is 15%. Among free, fresher first, older first, and mixed policies, the free policy provides the decision maker with more profit than the other three policies since it imposes less constraints on the model

Optimal Routing in Supply Chain Aimed at Minimizing Vehicle Cost and Supply

AbstractTransportation plays a vital role in supply chain. An inefficient transportation system disrupts supply chain and imposes severe damages to it. This paper investigates a transportation model with a limited number of vehicles with different capacities. The vehicles are used to handle raw and semi-finished materials from contractors’ warehouses to the main factories and to transport finished products to the warehouses of the distribution companies. The main purpose was to cover all transportation requests in a manner that it results in a reduced transportation cost, a reduced use of rental vehicles, and a reduced stopping duration of vehicle in destinations through the optimal use of available resources. In the considered model, first, a web-based system was designed in order to enable the registration of handling requests in the system with the purpose of compensating vehicle shortage. The handling requests are confirmed by drivers and transportation companies through SMS, email, and internet. Then, the proposed model performs network routing in order to completely cover the transportation network and to reduce transportation costs and vehicles stopping duration in destination. Finally, the model was run in different conditions, and the possibility of increasing vehicles with the purpose of reducing costs was studied