Optimization problems due to noisy data are usually solved using stochastic programming or robust optimization approaches. Both requiring the explicit characterization of an uncertainty set that models the nature of the noise. Such approaches tightly depend on the modeling of the uncertainty set. In this paper, we introduce a framework that implicitly models the uncertain data. We define the ge...

Although current technologies allow simple online banking transactions, it is vital to guarantee access bank branches both for customers and businesses. Banking branch interactions improve trust in institutions everyday situations emergencies. This research addresses the problem of location facilities. A set objective functions related socio-economic variables, geographical coverage bankers pre...

This paper considers knapsack problem with fuzzy weights, says fuzzy knapsack problem (FKP). Here we introduce possibility index which gives the possibility of choosing the items with fuzzy weights for knapsack with crisp capacity. In this paper a dynamic programming technique has been introduced to optimize the utility value of objective function. An algorithm has been proposed which gives the...

In this paper, we introduce the COmbinatorial Multi-Objective Multi-Armed Bandit (COMOMAB) problem that captures the challenges of combinatorial and multi-objective online learning simultaneously. In this setting, the goal of the learner is to choose an action at each time, whose reward vector is a linear combination of the reward vectors of the arms in the action, to learn the set of super Par...

In this paper we study a particular version of the stochastic knapsack problem with normally distributed weights: the two-stage stochastic knapsack problem. In contrary to the single-stage knapsack problem, items can be added to or removed from the knapsack at the moment the actual weights come to be known (second stage). In addition, a probability constraint is introduced in the first stage in...

In this work the Purchasing Scheduling Problem (PSP) is presented, based in study cases of public and private sectors. PSP models the purchasing process in both scenarios through an optimization approach. It is based on the multi-objective formulation of the knapsack problem. Therefore, PSP is defined as a based-graph problem with two objectives: maximization of satisfied demands and minimizati...

The multiple-choice multi-period knapsack problem sits in the interface of multiple choice programming and knapsack problems. Previous studies of this problem had attempted to find its optimal solution through the branch-and-bound procedure using special-ordered-sets. In this paper, we propose another solution approach based on the dynamic programming to locate its optimal solution through the ...

New variants of greedy algorithms, called advanced greedy algorithms, are identified for knapsack and covering problems with linear and quadratic objective functions. Beginning with single-constraint problems, we provide extensions for multiple knapsack and covering problems, in which objects must be allocated to different knapsacks and covers, and also for multi-constraint (multi-dimensional) ...