We are concerned with evolutionary algorithms that are employed for economic modeling purposes. We focus in particular on evolutionary algorithms that use a binary encoding of strategies. These algorithms, commonly referred to as genetic algorithms, are popular in agent-based computational...

Revenue management is the practice of selecting those customers that generate the maximum revenue from a fixed and perishable capacity. Cargo revenue management differs from the well-known passenger revenue management problem by the fact that its capacity constraint is 2-dimensional, i.e. weight...

We describe an algorithmic approach to determine an efficient railway rolling stock circulation ona single line or on a set of interacting lines. Given the timetable and the passengers? seatdemand, we develop a branch-and-price algorithm that results in an allocation of rolling stockmaterial to...

We present structural and computational investigations of a new class of weak forecast horizons - minimal forecast horizons under the assumption that future demands are integer multiples of a given positive real number - for a specific class of dynamic lot-size (DLS) problems. Apart from being...

Many e-tailers providing attended home delivery, especially e-grocers, offer narrow delivery time slots to ensure satisfactory customer service. The choice of delivery time slots has to balance marketing and operational considerations, which results in a complex planning problem. We study the...

In this work, we solve a real-world facility location problem by means of a mixed integer linear programming model. The problem is faced by an Italian multi-utility company operating in the sector of waste management. The company works in several Italian regions to collect and treat the urban...