Smooth implementation and controlling conflicting goals of a project with the usage of all related resources through organization is inherently a complex task to management. At the same time deterministic models are never efficient in practical project management (PM) decision problems because the related parameters are frequently fuzzy in nature. The project execution time is a major concern o...

The paper discusses the location-allocation model for logistic networks and distribution centers through considering uncertain parameters. In real-world cases, demands and transshipment costs change over the period of the time. This may lead to large cost deviation in total cost. Scenario based robust optimization approaches are proposed where occurrence probability of each scenario is not know...

this paper considers the fuzzy inventory model for deteriorating items for power demand under fully backlogged conditions. we define various factors which are affecting the inventory cost by using the shortage costs. an intention of this paper is to study the inventory modelling through fuzzy environment. inventory parameters, such as holding cost, shortage cost, purchasing cost and deteriorati...

warranty as a kind of service contract today plays a role key in business and legal transactions. in this paper, we present a manufacturer, an agent and a customer's model under different service contracts suggestions. the manufacturer's profit is maximized by determining sale price, warranty period and warranty price. in addition we obtain optimal maintenance cost or repair cost for ...

this paper is a research on the ordering planning of a supply chain with one supplier, multi buyer and multi deteriorating items. items have fixed life time and expire dates. the ordering period is taken as variable and must be computed the proposed models. the problem is studied via two different approaches the first is the joint replenishment, based on the hwang and chew's model [3] and ...

nowadays, software cost estimation (sce) with machine learning techniques are more performance than other traditional techniques which were based on algorithmic techniques. in this paper, we present a new hybrid model of multi-layer perceptron (mlp) artificial neural network (ann) and ant colony optimization (aco) algorithm for high accuracy in sce called multilayer perceptron ant colony optimi...

fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. in this research, fcm is chosen for fuzzy clustering. parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. these two parameters require tuning to reduce the overfitting in the...