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Abstract: This study deals with berth allocation for Maritime Autonomous Surface Ships (MASSs) in the context of the mixed operation of MASSs and manned vessels from the perspective of port-shipping companies’ collaboration. Two berth allocation strategies, namely the separated-type and the mixed-type, are proposed in this article. Two mixed integer nonlinear programming models aimed at minimizing the total docking cost of the vessels in the port and the waiting time for berths are developed and solved using Gurobi, respectively. A large-scale simulation of the mixed-type berth allocation model is carried out using an improved simulated annealing algorithm. Several experiments are conducted to test the effectiveness of the model and to draw insights for commercializing autonomous vessels. The presented results show that multi-objective modeling and optimization should be conducted from the collaboration of port-shipping companies, which is more efficient from the perspective of shipping companies or ports, respectively. When berth resources are limited or there is a high requirement for operational safety, the separated-type berth allocation strategy is more efficient. When the number of MASS-dedicated berths reaches a certain proportion, the total docking cost of the vessel no longer changes, indicating that more dedicated berths are not better.
Keywords: maritime autonomous surface ship (MASS), mixed operation scenarios, berth allocation, mixed integer programming, simulated annealing algorithm, port-shipping companies’ collaboration
Published in DKUM: 18.06.2025; Views: 0; Downloads: 0
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Abstract: Background: City logistics is a critical component of urban economic development, as it optimizes supply chains, enhances customer satisfaction through reliable deliveries, and minimizes environmental impacts in densely populated areas. This field addresses various challenges, including traffic congestion, environmental concerns, noise pollution, and the crucial need for timely deliveries. Routing and scheduling are central to logistics operations, with modern software integrating time windows to meet precise scheduling demands driven by detailed customer requirements and operational efficiencies. Furthermore, advanced vehicle routing models now effectively simulate real-world factors such as traffic congestion, stochastic travel times, and dynamic product demands. Purpose: This paper aims to develop an algorithm that addresses the routing decisions. Our approach extends to the time dimension, considering travel times and customer service times within predefined time windows. Study design/methodology/approach: The proposed algorithm is structured to execute in iterative phases, aiming to optimize key logistical objectives. In order to generate competitive solutions, we seek to minimize the number of vehicles utilized and overall travel costs. The evaluation of solution space was conducted via Simulated Annealing. Findings/conclusions: The performance of the proposed algorithm, evaluated using the Gehring and Homberger benchmark instances for 200 customers, demonstrates its effectiveness. The algorithm successfully meets the target number of vehicles required, and the associated travel costs are on average within 1% of the best solutions reported in the relevant literature. Limitations/future research: Given the ongoing need for timely solutions from decision-makers, future research endeavors will focus on enhancing the computational efficiency of the algorithm. Additionally, incorporating more time-related features, such as stochastic travel times, could further improve the algorithm's real-time applicability.
Keywords: city logistics, vehicle routing, simulated annealing, time windows, scheduling
Published in DKUM: 27.03.2025; Views: 0; Downloads: 2
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Abstract: This paper presents a discrete-event simulation (DES) approach for simulation of distributed energy resources (DER). The DES approach provides means to adapt the energy workloads of the system according to any variations of demands that can occur due to temperature regulation requirements or operational demands. Along with a basic model based on a concrete DER configuration, additional models are presented and analysed in order to demonstrate the adaptability of the DES approach to analyse alternative configurations. The models were tested on historical energy consumption data in order to provide the expected workloads and costs. Models are capable to predict the amount of three different energies and cost for the company based on the inside and outside temperatures.
Keywords: cost, discrete-event simulation, distributed energy resources, energy efficiency, hospitals, logistics
Published in DKUM: 10.03.2025; Views: 0; Downloads: 8
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Abstract: V raziskavi smo si pogledali in raziskali problematiko skladiščenja in skladiščnih procesov v podjetju ZETA Holding na avstrijskem Štajerskem, natančneje v Liebochu, kjer proizvodni proces temelji na projektnih delih, kar pomeni potrebo po veliki prilagodljivosti skladiščenja. Ker se podjetje v zadnjih letih srečuje z rastjo in povečano proizvodnjo, je prišlo do težav in pomanjkanja skladiščnih prostorov ter ustrezne manipulacije. Pomanjkljivosti se odražajo tudi v samih skladiščnih sistemih in načinih skladiščenja. V ta namen smo raziskali različne pristope k reševanju omenjenega problema in trg sodobnih skladiščnih sistemov ter možnosti za njihovo uporabo. Hkrati potrebujemo za sodobne skladiščne sisteme različne vrste manipulativnih sredstev, ki smo jih s pomočjo izkušenj in znanj poiskali pri različnih dobaviteljih ter s tem poiskali najprimernejše izvedbe le-teh. Na koncu smo raziskave združili in poiskali optimizirano rešitev skladiščenja z najprimernejšimi manipulativnimi sredstvi tako, da smo maksimalno izkoristili velikost razpoložljivih skladiščnih prostorov.
Keywords: skladiščni proces, skladiščenje, MRP, manipulacijska sredstva
Published in DKUM: 27.11.2024; Views: 0; Downloads: 20
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Abstract: The outbreak of COVID-19 caused many changes in people's life. One of the most significant is the travel behaviour and transport mode choice. This study focus on the changes that the inhabitants of Vienna made in their travel choices because of the virus. The same research about spatial modelling the transport mode choice of commuters in Vienna was completed in 2019 and is a topic addressed in our previous work. Based on our developed methodology, this article indicates that public transport is not a dominant transport mode choice as it was before the virus outbreak.The main result of this paper is geographically defined areas of application of individual alternatives shown on the final map of modal shift in Vienna, which could provide theoretical support for policy-makers and transportation planners. For the city of Vienna, we found that the area of the city where cars are now used has increased, which certainly has a negative impact on air quality and life in the city. The advantage of the methodology is that it can also be applied to other cities in the world.
Keywords: coronavirus, city traffic, urban mobility, transport mode choice, passenger transport, geographical methods, spatial modelling, city logistics, Vienna
Published in DKUM: 14.10.2024; Views: 0; Downloads: 21
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