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Hazardous materials routing and scheduling decisions involve the determination of the minimum cost and/or risk routes for servicing the demand of a given set of customers. This paper addresses the bicriterion routing and scheduling problem arising in hazardous materials distribution planning. Under the assumption that the cost and risk attributes of each arc of the underlying transportation network are time-dependent, the proposed routing and scheduling problem pertains to the determination of the non-dominated time-dependent paths for servicing a given and fixed sequence of customers (intermediate stops) within specified time windows. Due to the heavy computational burden for solving this bicriterion problem, an alternative algorithm is proposed that determines the k-shortest time-dependent paths. Moreover an algorithm is provided for solving the bicriterion problem. The proximity of the solutions of the k-shortest time-dependent path problem with the non-dominated solutions is assessed on a set of problems developed by the authors.

Most of the busiest airports worldwide experience serious congestion and delay problems which call for some immediate capacity and demand management action. Solutions aiming to manage congestion through better slot scheduling have lately received a great deal of consideration due to their potential for delivering quick and substantial capacity utilisation improvements. A slot scheduling approach brings promises to cope better with congestion problems in the short to medium run and in a more sustainable way based on existing resources. This paper aims to provide a critical review of current research in declared capacity modelling and strategic slot scheduling. Furthermore, it goes beyond the critical review of current research developments by identifying future research issues and gaps and developing concrete directions towards modelling and solving advanced single airport and network-based slot scheduling problems. Our research findings suggest that the next generation of slot scheduling models should explore variations of currently used objectives (e.g., alternative expressions of schedule delay) and most importantly enrich them with fairness and equity, resource utilisation and environmental considerations. Future modelling efforts should also aim to further investigate airlines' utility of alternative slot allocation outcomes, including various acceptability measures and levels of tolerance against schedule displacements. Last but not least, future research should intensively focus on the development and validation of computationally viable and robust slot scheduling models being able to capture the complexity, dynamic nature and weather-induced uncertainty of airport operations, along with hybrid solution approaches being able to deal with the size and complexity of slot allocation at network level.

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