Knapsack cover inequalities are among the most frequently used cuts for solving 0-1 linear programs. In this paper, we propose adaptations of these classical valid inequalities to the case when knapsack items have uncertain weights. For modeling uncertainty, we focus on the robust framework proposed by Bertsimas and Sim (2003). Then, a robust version of the bandwidth packing problem is consider...

A fuzzy random model of Combined Location Routing and Inventory Problem (CLRIP) has been presented with continuous review inventory policy in B2C distribution environment for the first time. Demands of customers and distribution centers are uncertain and have been assumed to be fuzzy random variables. To solve the model, first the expected value of fuzzy random variable and the possibilistic me...

Modelling complex systems such as multiple-use reservoirs can be challenging. A legitimate question for scientists and modellers is how best to model their management under uncertain rainfall. This paper studies whether it is worth using a stochastic model that requires more effort than a much simpler deterministic model. Both models are applied to the management of a multiple-use reservoir in ...

We present mixed integer linear programming models that are robust in the face of uncertain traffic demands known to lie in a certain polyhedron for the problem of dense wavelength division multiplexing network routing and provisioning at minimal cost. We investigate the solution of the problem in a set of numerical experiments for two models of polyhedral uncertainty: (a) the hose model, (b) a...

<p style='text-indent:20px;'>This paper studies the pricing and recycling decision problems in a closed-loop supply chain (CLSC) containing manufacturer, downstream retailer, third-party left. The manufacturer is subjected to cap-and-trade regulation determines wholesale price of products carbon emission reduction rate. retailer its resale meet customer demands. left collection rate reman...

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...

It is important to design multi-energy supply systems optimally in consideration of their operations for variations energy demands. An approach efficiently solving such an optimal problem with a large number periods demands derive approximate solution by time series aggregation. However, does not provide any information on the accuracy value objective function. In this paper, effective aggregat...