Due to the nature of agricultural and food industry, management production, storage, transportation, waste disposal environmental effects their are great importance. To deal with sustainability issues linked supply chains, we propose in this study a mathematical model design sustainable chain highly perishable product (strawberry). The is multiperiod, multiproduct multiobjective MINLP program t...

This paper gives a brief introduction into multiple objective programming support. We will overview basic concepts, formulations, and principles of solving multiple objective programming problems. To solve those problems requires the intervention of a decisionmaker. That’s why behavioral assumptions play an important role in multiple objective programming. Which assumptions are made affects whi...

COVID-19's developing trend has put the waste management systems of governments all over world in jeopardy. The increasing rise infectious medical now become a serious problem. This paper presents multi-period multi-objective model for designing system during COVID-19 pandemic. aims to reduce total costs while also reducing environmental impact treatment centers, disposal and transportation. It...

Most of the real life classification problems have ill defined, imprecise or fuzzy class boundaries. Feedforward neural networks with conventional backpropagation learning algorithm are not tailored to this kind of classification problem. Hence, in this paper, feedforward neural networks, that use backpropagation learning algorithm with fuzzy objective functions, are investigated. A learning al...

We explore an approach to possibilistic fuzzy c-means clustering that avoids a severe drawback of the conventional approach, namely that the objective function is truly minimized only if all cluster centers are identical. Our approach is based on the idea that this undesired property can be avoided if we introduce a mutual repulsion of the clusters, so that they are forced away from each other....

This paper proposes a qualitative approach to solve multicriteria decision making problems under possibilistic uncertainty. Depending on the decision maker attitude with respect to uncertainty (i.e. optimistic or pessimistic) and on her attitude with respect to criteria (i.e. conjunctive or disjunctive), four ex-ante and four ex-post decision rules are defined and investigated. In particular, t...

This paper considers new downside risk-aversion models for linear optimization (linear programming) with discrete fuzzy random variables. Through new downside risk measures for fuzzy stochastic optimization problems, possibilistic low partial moment (PLPM) models are constructed by incorporating possibility and necessity measures into classical low partial moment. To provide practical models, t...