Shared autonomous vehicle (SAV) is expected to become an essential transportation mode. However, the studies on its scheduling and routingproblems are all based on peer-to-peer (P2P) service, which refers to a pickup...
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Shared autonomous vehicle (SAV) is expected to become an essential transportation mode. However, the studies on its scheduling and routingproblems are all based on peer-to-peer (P2P) service, which refers to a pickup and delivery on a single trip. The P2P service ignores the correlations between sub-trips and users' journey continuity. To address this problem, a trip-chain based (TCB) service is proposed in SAV system, where users can choose paying and keep SAVs (PKSS) with no waiting time. Furthermore, based on the network flow theory, an integer linear programming model was established to decide optimal SAV's routing and scheduling. Finally, experiments are conducted in Beijing, China. Compared with the P2P service, the TCB service can not only increases operators' profitability but also reduces users' waiting time, provided that the operators set the price for PKSS between 0.1 and 0.65 CNY per minute.
Liquefied natural gas (LNG) is playing a prominent role in current global maritime transport and port operations. The industry, in which a wide range of agents are involved, is expanding rapidly. However, applied rese...
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Liquefied natural gas (LNG) is playing a prominent role in current global maritime transport and port operations. The industry, in which a wide range of agents are involved, is expanding rapidly. However, applied research into LNG operations research (OR) is still in its infancy. The goal of this investigation is to assess the literature that deals with OR LNG logistics chains. Existing studies fall into two groups: those that consider pricing as the most important factor;and those that focus on the inventory and routingproblem (IRP) and the routing and scheduling problem (RSP). Our review of the literature reveals that there are seven emergent areas of research which are linked to the use of new programming paradigms, the introduction of climate factors and possible changes in trade flow patterns caused by factors such as the widening of the Panama Canal or the opening of the Arctic Bridge.
Electric vehicles have recently received increasing attention because of their positive environmental and economic impacts;however, such vehicles are still not gaining widespread popularity for practical use given the...
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Electric vehicles have recently received increasing attention because of their positive environmental and economic impacts;however, such vehicles are still not gaining widespread popularity for practical use given the inconvenience of limited battery capacity and long recharge times. To compensate for these drawbacks, plug-in hybrid electric vehicles (PHEVs) have been proposed, which can be recharged using standard household plug-in sockets unlike normal hybrid vehicles. Thus, PHEVs can run for long distances using widely available electrical power. scheduling routes for the efficient use of electrical power is essential for PHEVs to succeed. Therefore, in this paper, we consider the PHEV routing and scheduling problem. We first formulate this problem as a mixed-integer programming (MIP) problem. Next, we propose three algorithms using a labeling method for large-scale problems;an exact algorithm and two heuristic algorithms. Our computational experiments show that the routes obtained using our algorithms are cost-efficient;further, our heuristic algorithms are much faster than the MIP formulation.
This paper presents the home health care routing and scheduling problem as the vehicle routingproblem with time windows (VRPTW). we propose a dynamic approach for home care planning to ensure the continuity of care f...
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This paper presents the home health care routing and scheduling problem as the vehicle routingproblem with time windows (VRPTW). we propose a dynamic approach for home care planning to ensure the continuity of care for patients. The proposed approach aims to optimize the care plan route of each caregiver according to their skills, availabilities and preferences. We aim also to minimize the violation of time windows in order to maximize patient and caregiver's satisfaction. The optimal plan route is generated with a population-based algorithm which is the Artificial Immune Algorithm (AIS). A multi-agent approach is used to ensure communication and coordination between the different actors. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the CENTERIS -International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies.
In recent years, Home Health Care (HHC) has gained popularity in different countries around the world (e.g. France, US, Germany, etc.). The HHC consists in providing medical services to patients at home. During the HH...
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In recent years, Home Health Care (HHC) has gained popularity in different countries around the world (e.g. France, US, Germany, etc.). The HHC consists in providing medical services to patients at home. During the HHC service, caregivers' planning may be disrupted by some unexpected events (e.g. urgent request, caregiver absence, traffic congestion, etc.), which makes HHC activities infeasible. This paper addresses the daily HHC routing and scheduling problem by considering unpredicted events. To solve this problem, we propose a Case-Based Reasoning (CBR) methodology. Our purpose is to create the HHC case base which contains the knowledge about the perturbation. Copyright (C) 2022 The Authors.
Planning effective itineraries for tourists is a major problem that has been gaining attention over the last years. This paper proposes a new bi-objective integer linear programming model for this problem. Decisions i...
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Planning effective itineraries for tourists is a major problem that has been gaining attention over the last years. This paper proposes a new bi-objective integer linear programming model for this problem. Decisions include the choice of the best itinerary to be performed considering multi-period routing, time windows for the visited attractions and the choice of restaurants and hotels. The conflicting objectives considered are: (i) maximizing the level of service offered by the itinerary, and (ii) minimizing the total distance traveled. The problem resolution, even for small instances by exact methods, is limited. This motivated the proposition of a new customized MIP-heuristic based on decomposition, fix-and-optimize and MIP-start, to produce good -quality solutions with moderate computational effort. Tchebycheff's scalarization method was coupled to this heuristic and multiple compromise solutions were obtained. Extensive results with problem instances of different sizes and characteristics showed a good performance of this approach, capable of producing effective solutions within short runtimes. The analysis of the solutions indicated a strong conflict between the objectives, allowing the user to quantify the losses and gains when one criterion is prioritized over the other. A brief sensitivity analysis of some model parameters revealed interesting managerial insights. Some examples include quantifying the negative impacts in terms of the level of service offered by concentrating hotels and restaurants in the center of tourist attractions, increasing visit and transfer times between attractions and reducing the planning horizon for the entire itinerary. These aspects validate the potential of using this MIP model and applying this MIP-heuristic in real situations.
The basic input data for any vehicle routing models are travel time, distances, and cost between nodes in the network. Information on these basic data is not always accurate, since many factors affect the condition of...
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The basic input data for any vehicle routing models are travel time, distances, and cost between nodes in the network. Information on these basic data is not always accurate, since many factors affect the condition of vehicle travel. Travel time on an urban road network may be considered 'fuzzy', since its estimate is often subjective and it can be controlled by the driver to some extent. Developing vehicle routes, hence, must incorporate the fuzziness of travel time in the network. In this paper, a vehicle routing model which treats travel times between nodes as a 'fuzzy' number is introduced. Assuming that all the travel times between nodes are fuzzy numbers, the proposed model follows the principles of the classical Clarke-Wright algorithm to develop a set of vehicle routes. The examples presented show that the route pattern of each vehicle varies considerably with the degree of fuzziness of travel time. This suggests that depending upon the dispatcher's level of confidence about the travel time, different vehicle route patterns can be developed.
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