in many practical distribution networks, managers face significant uncertainties in demand, local price of building facilities, transportation cost, and macro and microeconomic parameters. this paper addresses design of distribution networks in a supply chain system which optimizes the performance of distribution networks subject to required service level. this service level, which is considere...

Large scale dispatching problems are technically characterized as classical NP-hard problems which means that they cannot be solved optimally with existing methods in a polynomial time. Benders decomposition is recommended for solving large scale Mixed Integer Programming (MIP). In this paper we use the Bender Decomposition technique for reformulating the Ready Mixed Concrete Dispatching Proble...

This paper describes a complete and efficient solution to the stochastic allocation and scheduling for Multi-Processor System-on-Chip (MPSoC). Given a conditional task graph characterizing a target application and a target architecture with alternative memory and computation resources, we compute an allocation and schedule minimizing the expected value of communication cost, being the communica...

The problem addressed in this paper is related to an aerospace company seeking to change its outsourcing strategies in order to meet the expected demand increase and customer satisfaction requirements regarding delivery dates and amounts. A bilinear goal programming model is developed to achieve the company’s objectives. A modified Benders decomposition method is successfully applied to handle ...

Multistage stochastic linear programming has many practical applications for problems whose current decisions have to be made under future uncertainty. There are a variety of methods for solving the deterministic equivalent forms of these dynamic problems, including the simplex and interior point methods and nested Benders decomposition { which decomposes the original problem into a set of smal...

in this paper, a multi-objective hub location problem considering stochastic links and candidate nodes characteristics is modeled. the first objective is to minimize total costs, including setup and transportation costs. the second one is to minimize network risks. characteristics such as weather conditions, safety, exchange rate, crisis, are defined as uncertainty parameters and considered as ...

In this paper, the resilient-constrained generation and transmission expansion planning (RCGTEP) considering natural disasters such as earthquake flood is presented. The proposed model contains a two objective problem that first function minimizes construction operation costs of resiliency sources (RSs) and, in second function, minimization expected energy not supplied (EENS) due to outage syst...

We present a branch-and-bound algorithm for discretely-constrained mathematical programs with equilibrium constraints (DC-MPEC). This is a class of bilevel programs with an integer program in the upper-level and a complementarity problem in the lower-level. The algorithm builds on the work by Gabriel et al. (2010) and uses Benders decomposition to form a master problem and a subproblem. The new...

This paper presents a method that combines Benders decomposition and column generation to solve the multi-activity tour scheduling problem. The Benders decomposition approach iterates between a master problem that links daily shifts with tour patterns and a set of daily subproblems that assign work activities and breaks to the shifts. Due to its structure, the master problem is solved by column...