Service of SURF
© 2025 SURF
The two-dimensional vehicle routing problem (2L-VRP) is a realistic extension of the classical vehicle routing problem where customers’ demands are composed by sets of non-stackable items. Examples of such problems can be found in many real-life applications, e.g. furniture or industrial machinery transportation. Often, these real-life instances have to deal with uncertainty in many aspects of the problem, such as variable traveling times due to traffic conditions or customers availability. We present a hybrid simheuristic algorithm that combines biased-randomized routing and packing heuristics within a multi-start framework. Monte Carlo simulation is used to deal with uncertainty at different stages of the search process. With the goal of minimizing total expected cost, we use this methodology to solve a set of stochastic instances of the 2L-VRP with unrestricted oriented loading. Our results show that accounting for systems variability during the algorithm search yields more robust solutions with lower expected costs.
This review evaluates the methodological quality of current front-of-pack labeling research and discusses future research challenges. Peer-reviewed articles were identified using a computerized search of the databases PubMed andWeb of Science (ISI) from1990 to February 2011; reference lists fromkey published articleswere used as well. The quality of the 31 included studies was assessed. The results showed that the methodological quality of published front-of-pack labeling research is generally low to mediocre; objective observational data-based consumer studies were of higher quality than consumer studies relying on self-reports. Experimental studies that included a control group were lacking. The review further revealed a lack of a validated methodology to measure the use of front-of-pack labels and the effects of these labels in real-life settings. In conclusion, few methodologically sound front-of-pack labeling studies are presently available. The highest methodological quality and the greatest public health relevance are achieved by measuring the health effects of front-of-pack labels using biomarkers in a longitudinal, randomized, controlled design in a real-life setting.
LINK