We survey structural properties of and algorithms for stochastic integer programming models, mainly considering linear two-stage models with mixedinteger recourse (and their multi-stage extensions).

In real-life scenarios, there are many mathematical tools to handle incomplete and imprecise data. One of them is the fuzzy approach. The main issue with addressing nonlinear interval programming (NIP) problems that optimal solution problem a decision made under uncertainty has risk not satisfying feasibility optimality criteria. Some strategies this kind using classical terminology such as fea...

This research article aims to study a multi-objective linear fractional programming (FMOLFP) problem having fuzzy random coefficients as well pseudorandom decision variables. Initially, the FMOLFP model is converted single objective (FLP) model. Secondly, we show that optimal solution of an FLP resolved into class relative (LP) As result, some theorems LP combined with series solutions problems...

A linearization technique is developed for multi-objective multi-quadratic 0-1 programming problems with linear and quadratic constraints to reduce it to multi-objective linear mixed 0-1 programming problems. The method proposed in this paper needs only O (kn) additional continuous variables where k is the number of quadratic constraints and n is the number of initial 0-1 variables.

Supplier selection is a multi-criteria problem which includes both tangible and intangible factors in these problems if suppliers have capacity or other different constraints two problems will exist: which suppliers are the best and how much should be purchased from each selected supplier? The objective of this paper is to present an integrated model and a supporting approach for effective ...

Most of the real-life decision-making problems have more than one conflicting and incommensurable objective functions. In this paper, we present a multiobjective two-stage stochastic linear programming problem considering some parameters of the linear constraints as interval type discrete random variables with known probability distribution. Randomness of the discrete intervals are considered f...