In this paper we present a unified (probabilistic/possibilistic) model for resource-constrained project scheduling problem (RCPSP) with uncertain activity durations and a concept of a heuristic approach connected to the theoretical model. It is shown that the uncertainty management can be built into any heuristic algorithm developed to solve RCPSP with deterministic activity durations. The esse...

objective: the current research is to investigate the relation between deterministic thinking and mental health among drug abusers, in which the role of  cognitive distortions is considered and clarified by focusing on deterministic thinking. methods: the present study is descriptive and correlative. all individuals with experience of drug abuse who had been referred to the shafagh rehabilitati...

In this paper, we propose a new model for designing integrated forward/reverse logistics based on pricing policy in direct and indirect sales channel. The proposed model includes producers, disposal center, distributers and final customers. We assumed that the location of final customers is fixed. First, a deterministic mixed integer linear programming model is developed for integrated logistic...

Perishability of blood products as well as uncertainty in demand amounts complicate the management of blood supply for blood centers. This paper addresses a mixed-integer linear programming model for blood platelets production planning while integrating the processes of blood collection as well as production/testing, inventory control and distribution. Whole blood-derived production methods for...

In dielectric breakdown, the phenomena of streamers formation and spontaneous branching is commonly observed. A deterministic negative streamer model is reviewed in this article. We recently have proposed that this reduced model is able to explain the branching phenomena, due to a Laplacian instability quite like in viscous fingering. Particular attention is paid to the physical interpretation ...

While standard procedures of causal reasoning as procedures analyzing causal Bayesian networks are custom-built for (non-deterministic) probabilistic structures, this paper introduces a Boolean procedure that uncovers deterministic causal structures. Contrary to existing Boolean methodologies, the procedure advanced here successfully analyzes structures of arbitrary complexity. It roughly invol...