This paper addresses a class of two-stage robust optimization models with integer adversarial variables. We discuss the importance of this class of problems in modeling two-stage robust resource planning problems where some tasks have uncertain arrival times and duration periods. We apply Dantzig-Wolfe decomposition to exploit the structure of these models and show that the original problem red...

Heuristic concentration (HC) is a two-stage metaheuristic that can be applied to a wide variety of combinatorial problems. It is particularly suited to location problems in which the number of facilities is given in advance. In such settings, the ®rst stage of HC repeatedly applies some random-start interchange (or other) heuristic to produce a number of alternative facility con®gurations. A su...

We consider the classic continuous-review N stage serial inventory system with a homogeneous Poisson demand arrival process at the most downstream stage (Stage 1). Any shipment to each stage, regardless of its size, incurs a positive fixed setup cost and takes a positive constant lead time. The optimal policy for this system under the long-run average cost criterion is unknown. Finding a good w...

The minimum shift design problem (MSD) is a scheduling problem that commonly arises in workforce management activities. Given a collection of shifts and workforce requirements, the problem consists in finding a minimum cardinality set of work shifts, and the number of workers to assign to each shift, in order to meet (or minimize the deviation from) prespecified staff requirements. This problem...

In this paper, two Benders decomposition algorithms and a novel two-stage integer programming-based heuristic are presented to optimize the beam angle and fluence map in Intensity Modulated Radiation Therapy (IMRT) planning. Benders decomposition is first implemented in the traditional manner by iteratively solving the restricted master problem and then identifying and adding the violated Bende...

This paper considers a two-stage flexible flowshop scheduling problem with no waiting time between two sequential operations of a job and no idle time between two consecutive processed jobs on machines of the second stage. We show its complexity and present a heuristic algorithm with asymptotically tight error bounds. © 2004 Elsevier B.V. All rights reserved.

This paper integrates multi-project scheduling and linear scheduling concepts. Since the problem is combinatorial, a two-stage heuristic solution-finding procedure is used to model the problem with multiple resource constraints. Simulated annealing is utilized as a searching engine in the second stage to find the probable optimized solution. The first stage is slightly different from the other ...

We consider a model of a two-stage push-pull production-distribution supply chain. The orders arrive at the final stage according to a Poisson process. Two separate operations, which take place at different locations with exponential service times, are required to convert the raw materials into finished goods. When the first operation is completed the intermediate inventory is held at the first...

The vehicle routing problem (VRP) is an important problem in the field of logistics management. As an NP-hard problem, the VRP real world sized instances cannot be solved to optimality within reasonable times. This research aims to develop a two-stage ant colony optimization (TACO) algorithm, which possesses a two-stage solution construction rule, to solve the large scale vehicle routing proble...