TWe perform a novel analysis of the fitness landscape of thejob-shop scheduling problem (JSP). In contrast to other well-known combinatorial optimization problems, we show that the landscape of the JSP is non-regular, in that the connectivity of solutions is variable.

In city logistics, service providers have to consider dynamics within logistics processes in order to achieve higher schedule reliability and delivery flexibility. To this end, city logistics routing demands for time-dependent travel time estimates and time-dependent optimization models. We...

Transportation service facilities often form system choke points with service rendered to entities from multiple queues that require staging for processing. With an MIP model that accommodates sequence-dependent setup times and processing times, we demonstrate how scheduling can be improved...

Delivery companies offer same-day delivery (SDD) in more and more cities. SDD defines a business model in which a customer order is fulfilled the same day it is issued. To gain a competitive advantage, companies start offering increasingly narrower delivery deadlines of a few hours length....

In this research we consider the problemof scheduling rounds of a non-professional table-tennisleague. We formalize the problem in terms of atimetabling optimization problem. Then we solve thishighly constrained problem with a permutation based GeneticAlgorithm for which feasibility preserving...

Many recent algorithmic approaches suffer from their limited applicability to dynamic scheduling scenarios. Genetic Algorithms have been shown to overcome this problem at the expense of searching less efficient. We propose a flexible dispatching procedure which is controlled by a Genetic...

In this paper we concentrate on Job Shop Scheduling as a representative of constrained combinatorial problems. We introduce a new permutation representation for this problem. Three crossover operators different in tending to preserve the relative order, the absolute order, and the position in...

The application of adaptive optimization strategies to scheduling in manufacturing systems has recently become a research topic of broad interest. Population based approaches to scheduling predominantly treat static data models, whereas real-world scheduling tends to be a dynamic problem. This...