Location-routing problems widely exist in logistics activities. For the biomass waste collection, there is a recognized need for novel models to locate the collection facilities and plan the vehicle routes. So far most location-routing models fall into the cost-driven-only category. However, comprehensive objectives are required in the specific context, such as time-dependent pollution and speed-and load-related emission. Furthermore, location-routing problems are hierarchical by nature, containing the facility location problems (strategic level) and the vehicle routing problems (tactical level). Existing studies in this field usually adopt computational intelligence methods directly without decomposing the problem. This can be inefficient especially when multiple objectives are applied. Motivated by these, we develop a novel multi-objective optimization model for the location-routing problem for biomass waste collection. To solve this model, we explore the way to tailor evolutionary algorithms to the hierarchical structure. We develop adapted versions of two commonly used evolutionary algorithms: the genetic algorithm and the ant colony optimization algorithm. For the genetic algorithm, we divide the population by the strategic level decisions, so that each subpopulation has a fixed location plan, breaking the location-routing problem down into many multi-depot vehicle routing problems. For the ant colony optimization, we use an additional pheromone vector to track the good decisions on the location level, and segregate the pheromones related to different satellite depots to avoid misleading information. Thus, the problem degenerates into vehicle routing problem. Experimental results show that our proposed methods have better performances on the location routing problem for biomass waste collection.

The floating liquefied natural gas (FLNG) system is an offshore facility that floats above a natural gas field, directly liquefying natural gas without the need for subsea pipelines. In recent years, there has been growing interest in exploring technological innovations for FLNG systems. As such, advancements could lead to breakthroughs in optimizing layout and operations within the limited space of these platforms. To address this, we first apply a patent mining method to cluster FLNG-related patent texts, identifying the key technological components. We then conduct a morphological analysis to pinpoint potential technological opportunities. In our case study, we identify seven such opportunities, which include a combination of plate-fin heat exchangers, horizontal LNG storage tanks, flexible flowlines, and tail loading methods. These findings offer valuable insights and directions for the future development of FLNG systems.

Introduction: Maritime chokepoint disruptions can substantially degrade shipping services even when the underlying network remains structurally connected. This study examines the Red Sea–Suez disruption and evaluates alternative recovery strategies. Methods: We develop a time-varying weighted shipping-network model incorporating load–capacity constraints, distance impedance, residual-capacity attraction, and cascading functional degradation, together with a route-reconfiguration model balancing transport cost, delay, and resilience. A synthetic scenario network calibrated with public data comprises 32 major Asia–Europe container ports and 134 directed links. Twenty simulations combine five disruption intensities with four operationally defined recovery strategies. An equal-budget capacity allocation experiment is also conducted under 75% corridor loss. Results: Under complete corridor loss, passive diversion reduces the service level Q to 0.827 and the effective-capacity index to 0.609, although the largest connected component remains intact and no port completely fails. Under 75% loss, joint optimization achieves the highest Q , whereas Cape rerouting has a lower generalized cost. Neither uniform nor alternative-path-targeted capacity expansion improves Q at three-decimal precision under the equal budget. Discussion: The capacity allocation result does not imply that port expansion is generally ineffective. Under the present model calibration, port handling capacity is not the binding constraint; fleet turnover emerges as the principal operational bottleneck. The framework provides a mechanism-based scenario platform that can be further validated using observed Automatic Identification System (AIS) and liner-schedule data.