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Based on commercial passenger-carrying airships like LZ129 or R100, a hypothetical electric rigid framed airship including a solar cell covered surface and a lithium-ion battery is designed. The size of the battery and the coverage with solar cells are selected such that long-haul flights are possible. To simulate flight times, weather data from 2019 and time-dependent solar irradiation are used. Travel route and battery use are optimised in order to reduce flight times. For a mid-range and long-haul use case for passenger or freight transport, travel times have been calculated. Building on these results, analysis of CO2 emissions, land-use, and operating costs are carried out to reveal that depending on the use case, CO2 emissions of solar-powered airships could be as low as 1% to 5% of the emissions of a conventional aircraft at an estimated energy consumption in USD per km of 0.5% to 2.5%.

Based on commercial passenger-carrying airships like LZ129 or R100, a hypothetical electric rigid framed airship including a solar cell covered surface and a lithium-ion battery is designed. The size of the battery and the coverage with solar cells are selected such that long-haul flights are possible. To simulate flight times, weather data from 2019 and time-dependent solar irradiation are used. Travel route and battery use are optimised in order to reduce flight times. For a mid-range and long-haul use case for passenger or freight transport, travel times have been calculated. Building on these results, analysis of CO2 emissions, land-use, and operating costs are carried out to reveal that depending on the use case, CO2 emissions of solar-powered airships could be as low as 1% to 5% of the emissions of a conventional aircraft at an estimated energy consumption in USD per km of 0.5% to 2.5%. [ABSTRACT FROM AUTHOR]

The optimal design of a suitable material supply process is important for the continuous, smooth operation of manufacturing processes, which includes the transportation and handling of work pieces, components, tools, equipment, pallets, packaging materials, and measuring instruments. The most common form of implementation of these material handling processes, especially in mass production, is the milkrun supply. In this paper, the author presents a method to optimise the milkrun material supply processes in manufacturing. The author gives a brief overview of research results related to milkrun-based material supply solutions. An Excel Solver-based optimization method is presented that is suitable to support the design of an optimal material supply process in any manufacturing environment by determining optimal material supply routes and optimal number of milkrun trolleys, depending on the supply demand, location of warehouse and manufacturing cells and the capacity of the milkrun trolleys. [ABSTRACT FROM AUTHOR]

Transportation enterprises have started to pay more attention to the vast amount of historical operational data. In this paper, real route information is extracted from the freight car trajectory data and a satisfied route is proposed based on this information. The satisfied route not only can reduce the travel cost but also conform to the actual transportation situation. A solution framework driven by trajectory data is developed to obtain the satisfied route. A case study associated with the Chinese railway is used to verify the model and the solution framework proposed in this paper. [ABSTRACT FROM AUTHOR]

The travelling salesman problem (TSP) is perhaps the most researched problem in the field of Computer Science and Operations. It is a known NP-hard problem and has significant practical applications in a variety of areas, such as logistics, planning, and scheduling. Route optimisation not only improves the overall profitability of a logistic centre but also reduces greenhouse gas emissions by minimising the distance travelled. In this article, we propose a simple and improved heuristic algorithm named 2-Opt++, which solves symmetric TSP problems using an enhanced 2-Opt local search technique, to generate better results. As with 2-Opt, our proposed method can also be applied to the Vehicle Routing Problem (VRP), with minor modifications. We have compared our technique with six existing algorithms, namely ruin and recreate, nearest neighbour, genetic algorithm, simulated annealing, Tabu search, and ant colony optimisation. Furthermore, to allow for the complexity of larger TSP instances, we have used a graph compression/candidate list technique that helps in reducing the computational complexity and time. The comprehensive empirical evaluation carried out for this research work shows the efficacy of the 2-Opt++ algorithm as it outperforms the other well-known algorithms in terms of the error margin, execution time, and time of convergence. [ABSTRACT FROM AUTHOR]

This study develops a cost model covering monetary and environmental damage costs for source-separated biowaste collection. The model provides an improved basis for decision-making by including environmental damage costs compared to the assessment that considers the only monetary cost. The monetary cost calculation integrated route optimisation using existing road networks, while the environmental damage cost was estimated using the life cycle impact assessment method based on the endpoint (LIME) model. The model was tested in the Finnish case where the new law implements the stricter requirement for source-separated biowaste. The costs of collection, transportation and treatment of three different scenarios were assessed: mixed waste under the old law (MW-OL), biowaste under the new law (B-NL) and mixed waste without biowaste under the new law (MW-NL). The results showed the economic and environmental benefits of sourced separated biowaste. The overall cost of collection and transportation (CT) under the old law and new laws were 80.7 € Mg−1 and 81.1 € Mg−1, respectively. Treatment costs were 79 € Mg−1 and 64.8 € Mg−1 under the old and new laws, respectively. The damage costs for CT under the old and new laws were 0.23 € Mg−1 and 0.24 € Mg−1, respectively. At the same time, the damage costs from the treatment stage were 4.9 € Mg−1 and 3.5 € Mg−1 under the old law and new law, respectively. The model supports decision-making when the collection scheme requires a change. Failing to plan an optimised solution and cost will lead to inefficient systems. [ABSTRACT FROM AUTHOR]

This paper describes the architecture of a weather routing system consisting of two key elements: onboard monitoring and route optimiser sub-systems. The former is responsible for collecting various onboard measurements, such as current ship position or ship motion variables. These data, when gathered and processed, are then used for fine-tuning a ship model. The model, together with weather forecasts, is utilised by a multi-objective route optimiser to estimate forecasted ship responses during the voyage. The route optimiser has been developed in a client-server architecture to reallocate all necessary high-tech resources to the server side and keep the client software as simple and light as possible. The system also includes a module responsible for optimising transmission costs, to reduce onboard transmission during the voyage. The entire solution has been deployed onboard the demonstrator ship ‘Monte da Guia’ and tested during its operations at sea.

• A novel method of municipal solid waste (MSW) collection route optimization. • Population-dependent waste generation calculation method using image processing. • The concept of linear MSW density: waste generation divided by road length. • Accurate modelling of the transport road length covered using linear MSW density. • Efficient novel optimization programming approach with less processing requirements. The city of Budapest produces approximately 680–700 000 tonnes of municipal solid waste every year, of which <2/3 is being recycled or used for energetic purposes, the rest ends up in a landfill. To combat this environmental and logistical problem the installation of a second waste incineration plant has been proposed in the south of the city. The only cost associated with fuel consumption in the case of waste to energy powerplants (WtE plants) is the transport cost, as the city council provides economic support for waste disposal. Since the transportation has a huge influence on the cost of opertation, logistical optimisation of the transport routes promises a direct impact on cost savings. In this study the logistical optimisation of the Southern Budapest area was carried out using image processing and logic based algorithm programming. As a result the optimal transport of 230 000 tonnes of municipal solid waste (MSW) was solved resulting in a 4 835.2 km monthly travel distance reduction.This value can be translated to 7 823 €/month cost, 9 459.6 kg/month CO 2 and 45.3 kg/month NO x emissions reduction in the urban areas. [ABSTRACT FROM AUTHOR]

The travelling salesman problem (TSP) is perhaps the most researched problem in the field of Computer Science and Operations. It is a known NP-hard problem and has significant practical applications in a variety of areas, such as logistics, planning, and scheduling. Route optimisation not only improves the overall profitability of a logistic centre but also reduces greenhouse gas emissions by minimising the distance travelled. In this article, we propose a simple and improved heuristic algorithm named 2-Opt++, which solves symmetric TSP problems using an enhanced 2-Opt local search technique, to generate better results. As with 2-Opt, our proposed method can also be applied to the Vehicle Routing Problem (VRP), with minor modifications. We have compared our technique with six existing algorithms, namely ruin and recreate, nearest neighbour, genetic algorithm, simulated annealing, Tabu search, and ant colony optimisation. Furthermore, to allow for the complexity of larger TSP instances, we have used a graph compression/candidate list technique that helps in reducing the computational complexity and time. The comprehensive empirical evaluation carried out for this research work shows the efficacy of the 2-Opt++ algorithm as it outperforms the other well-known algorithms in terms of the error margin, execution time, and time of convergence.

Mobility as a Service (MaaS) is a term coined for the development and implementation of multi-modal trip planner recommendation systems. Multi-modal journeys can include public transport, private transport and hire-able e-scooters which can beneficially augment public transport journeys. This study proposes and tackles a new and more general multi-modal multi-objective journey planning problem than considered previously. Our aim is to generate Pareto sets of multi-modal journeys which minimise the objectives of cost, travel time, inconvenience, CO 2 emissions, and calorie expenditure, as well as find journeys that optimally balance the trade-offs between them. Commuters can then choose between green, cheap, fast, car-free or convenient journeys. This work proposes implicit enumeration and heuristic algorithms which are analysed in terms of their theoretical time complexity, empirically in terms of solution time and optimality gap using a series of Manhattan and random structure transport networks. We show that our algorithms can generate solutions of equal quality to RAPTOR—a prominent existing journey planning algorithm. For this problem we reveal that the number of network nodes is a huge computational bottleneck, leading to the suggestion that future research can benefit from limiting the number of network nodes that are considered as transfer points. While our heuristic can generate good quality Pareto sets quicker than the enumeration procedure for the largest instances considered, we show that the enumeration procedure with pruning rules can still be the most effective strategy for this particular problem. • This work proposes a new multi-modal multi-objective journey planning problem. • Exact and heuristic solution algorithms are proposed with time complexity analyses. • Output Pareto sets include green, cheap, fast, car-free, and convenient journeys. • Ablation studies reveal the optimal and fastest algorithm configurations. • Transfer-point-sample based algorithms are suggested to address a main bottleneck. [ABSTRACT FROM AUTHOR]

The Australian urban construction electricity sector has witnessed a transformational effect in the use of small-scale solar photovoltaic (PV) systems in the past decade. Currently, Australia has one of the highest rates of rooftop solar PV users with over 20% of households connected. This will see a rapid growth in the volume of PV waste in the coming years when these PV systems come to their end-of-life or require replacement. The collection and transportation involved in solar PV waste treatment has a significant impact on the environmental sustainability of Australian cities while designing a holistic reverse logistic (RL) network may play an essential role in the reduction of the associated cost and environmental impacts. In this study, the Weibull distribution model is employed to forecast the PV waste in the next three decades in South Australia. The study further estimates the pollutant emission associated with the collection and transportation of the waste for recycling and recovery using hotspot analysis, location allocation modelling and vehicle routing problem. Generation of pollutants - Particulate Matter (PM), Carbon Monoxide (CO), Carbon dioxide (CO 2) and Nitrogen Oxides (NOx) associated with transport and energy consumption are estimated through three routing scenarios. Results indicate that, there will be 109,007 tons of PV waste generated in urban and suburban context in South Australia by 2050. Among the three routing scenarios generated, the third scenario with optimised transfer stations and an additional recycling facility showed more than 34% reduction in pollutant emission. Such additional PV waste management facilities require policy support and regulations to effectively manage solar PV waste treatment and logistics. • The Weibull distribution model is employed to forecast the loss of PV waste. • A total of over 109,007 tons of PV waste will be generated by 2050. • Pollutant emission associated with transportation of PV waste is estimated. • Pollutants-PM, CO, CO 2 and NOx are estimated through three routing scenarios. • The third scenario optimised showed up to over 34% reduction in pollutant emission. [ABSTRACT FROM AUTHOR]