A multi-criteria decision support system for a routing problem in waste collection

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A decision support system for a waste collection vehicle routing problem

The selective collection of municipal solid waste for recycling is a very complex and expensive process, where a major issue is to perform cost-efficient waste collection routes. Despite the abundance of commercially available software for fleet management, they often lack the capability to deal properly with sequencing problems and dynamic revision of plans and schedules during process execution. Our approach to achieve better solutions for the waste collection process is to model it as a vehicle routing problem, more specifically as a team orienteering problem where capacity constraints on the vehicles are considered, as well as time windows for the waste collection points and for the vehicles. The final model is called capacitated team orienteering problem with double time windows (CTOPdTW).We developed a genetic algorithm to solve routing problems in waste collection modelled as a CTOPdTW. The results achieved suggest possible reductions of logistic costs in selective waste collection.

Highly robust hydrogels via a fast, simple and cytocompatible dual crosslinking-based process

A highly robust hydrogel device made from a single biopolymer formulation is reported. Owing to the presence of covalent and non-covalent crosslinks, these engineered systems were able to (i) sustain a compressive strength of ca. 20 MPa, (ii) quickly recover upon unloading, and (iii) encapsulate cells with high viability rates.

Highly robust chitosan hydrogels via a fast, simple and biocompatible dual crosslinking-based process

Load-bearing soft tissues such as cartilage, blood vessels and muscles are able to withstand a remarkable compressive stress of several MPa without fracturing. Interestingly, most of these structural tissues are mainly composed of water and in this regard, hydrogels, as highly hydrated 3D-crosslinked polymeric networks, constitute a promising class of materials to repair lesions on these tissues. Although several approaches can be employed to shape the mechanical properties of artificial hydrogels to mimic the ones found on biotissues, critical issues regarding, for instance, their biocompatibility and recoverability after loading are often neglected. Therefore, an innovative hydrogel device made only of chitosan (CHI) was developed for the repair of robust biological tissues. These systems were fabricated through a dual-crosslinking process, comprising a photo- and an ionic-crosslinking step. The obtained CHIbased hydrogels exhibited an outstanding compressive strength of ca. 20 MPa at 95% of strain, which is several orders of magnitude higher than those of the individual components and close to the ones found in native soft tissues. Additionally, both crosslinking processes occur rapidly and under physiological conditions, enabling cellsâ encapsulation as confirmed by high cell survival rates (ca. 80%). Furthermore, in contrast with conventional hydrogels, these networks quickly recover upon unloading and are able to keep their mechanical properties under physiological conditions as result of their non-swell nature.

Comparison of single and multi-objective evolutionary algorithms for robust link-state routing

Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.

Optimização do processo de recolha de resíduos: desenvolvimento de ferramentas de investigação operacional para o problema de orientação de equipas com multi-restrições

Tese de Doutoramento em Engenharia Industrial e de Sistemas.

Genetic algorithms for the non emergency patients transport service

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the paper. The authors would like to thank Dr. Elaine DeBock for reviewing the manuscript.

Separation by thermal diffusion in a rotary column

A rotary thermal diffusion column with the inner cylinder rotating and the outer cylinder static was used to separate n-heptane-benzene mixtures at different speeds of rotation. The results show that the column efficiency depends on the speed of rotation. For the optimum speed the increase in efficiency relative to the static column was of the order of 8%. The role of the geometric irregularities in the annulus width on performance of the rotary column is also discussed.