Reverse logistics planning plays a crucial role in supply chain management. Stochasticity different parameters along with time horizon can be challenge solving reverse problems. This paper proposes multi-stage, multi-period lot sizing decisions under uncertainties. The main uncertain factors are return and demand quantities, quality. Moment matching method was adopted to generate discrete set o...

This paper proposes an integrated methodology and its solution for supplier selection problem. A twostage stochastic programming model and fuzzy TOPSIS methods are consolidated in this methodology. After pre-research phase, in the second part of the methodology, fuzzy TOPSIS is used for ranking potential suppliers considering qualitative data under fuzzy environment. In the third part of the me...

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).

emission trading is one of the famous mechanisms under kyoto protocol to control environmental pollution. the aim of this paper is to design a strategic supply chain network under emission trading scheme with inclusion of stochastic parameters and budget limitation. demand and price of carbon credits are considered as the important stochastic parameters influencing the supply chain network. in ...

This paper deals with two-stage and multi-stage stochastic programs in which the right-hand sides of the constraints are Gaussian random variables. Such problems are of interest since the use of Gaussian estimators of random variables is widespread. We introduce algorithms to nd upper bounds on the optimal value of two-stage and multi-stage stochastic (minimization) programs with Gaussian right...

This article aims to explain the Nested Benders algorithm for the solution of large-scale stochastic programming problems in a way that is intelligible to someone coming to it for the first time. In doing so it gives an explanation of Benders decomposition and of its application to two-stage stochastic programming problems (also known in this context as the L-shaped method), then extends this t...

In this study, a new stochastic model is proposed to deal with a multi-product, multi-period, multi-stage, multi-site production and transportation supply chain planning problem under demand uncertainty. A two-stage stochastic linear programming approach is used to maximize the expected profit. Decisions such as the production amount, the inventory level of finished and semi-finished product, t...

Probabilistic or stochastic programming is a framework for modeling optimization problems that involve uncertainty.In this paper, we focus on multi-objective linear programmingproblems in which the coefficients of constraints and the righthand side vector are fuzzy random variables. There are several methodsin the literature that convert this problem to a stochastic or<b...

This paper deals with a realistic multi-period liner ship fleet planning problem by incorporating stochastic dependency of the random and period-dependent container shipment demand. This problem is formulated as a multi-period stochastic programming model with a sequence of interrelated two-stage stochastic programming (2SSP) problems characterized ship fleet planning in each single period. A s...