Crew Assignment with Duty Time Limits for Transport Services: Tight Multicommodity Models

2021 ◽  
Author(s):  
Anantaram Balakrishnan ◽  
Prakash Mirchandani ◽  
Sifeng Lin
Keyword(s):  
Real Life ◽  
Urban Transport ◽  
Optimization Approach ◽  
Integer Optimization ◽  
Solution Approach ◽  
Time Limits ◽  
Transport Services ◽  
Transit Agencies ◽  
Problem Instances ◽  
Duty Time

Modeling Crew Assignments for Urban Transport Services Using Differentiated Flows Public transit agencies need to judiciously deploy their limited crew members to operate numerous daily scheduled services, while meeting duty and working time regulations for each crew member. Since crew costs account for a large portion of the organizations’ operating expenses, minimizing the total crew and transfer costs is very important. But, with hundreds of daily trips and millions of possible crew itineraries, optimizing trip-to-crew assignment decisions is challenging. In “Crew Assignment with Duty Time Limits for Transport Services: Tight Multicommodity Models,” Balakrishnan, Mirchandani, and Lin propose a novel integer optimization model that represents itineraries as multicommodity flows, differentiated by first trip and depot, to capture the duty time limits and incorporate additional requirements such as selecting equitable schedules. The authors show that this compact model can be tighter than previous formulations, further strengthen the model, and propose a restricted optimization approach combined with an optimality test to generate near-optimal solutions quickly. Extensive computational tests using well-known and real-life problem instances show that the proposed model and solution approach can be very effective in practice.

scholarly journals Financing public transport: a spatial model based on city size

2017 ◽  
Vol 26 (1) ◽  
pp. 112-122
Author(s):  
Miguel Ruiz-Montañez
Keyword(s):  
Public Transport ◽  
Spatial Model ◽  
Metropolitan Areas ◽  
Real Life ◽  
Urban Transport ◽  
City Size ◽  
Transport Networks ◽  
Content Type ◽  
Transport Services ◽  
The City

Purpose The purpose of this paper is to investigate the relationships between public transport services and the financial needs. Cities require to be equipped with public transport networks as they are primarily responsible for creation of wealth for countries and to ensure sustainability of urbanization. Once decisions have been taken to design, build and operate such networks, it is equally important to set rules for urban transport financing. Depending on the city size and other factors, authorities allocate resources. Nonetheless, is there a relationship between the size of the city and its public transport financial needs? This paper develops a model to explain such relationships. Design/methodology/approach The study develops a spatial model, while providing intuition through the use of graphs, to solve the question of the amount of resources allocated for financing the transport services. Findings It is verified that those financial needs are more than proportional to the size of the city; when a city grows in its number of boroughs, economic funds needed to support public transport have to increase in a greater proportion in comparison to the growth of boroughs growth. The model states a formula valid for explaining the financial needs. Originality/value The model is interesting as it explains why large metropolitan areas need special financial aid from authorities. Real life shows that big cities like Paris, Berlin or Madrid need extraordinary funds for this purpose, and in most of the cases, specific national laws are required for financing public transport networks in these large metropolitan areas.

Risk-Based Robust Bidding Strategies for EVs’ Aggregators in Day-ahead Markets with Uncertainty

2020 ◽  
Author(s):  
Ahmed Abdelmoaty ◽  
Wessam Mesbah ◽  
Mohammad A. M. Abdel-Aal ◽  
Ali T. Alawami
Keyword(s):  
Robust Optimization ◽  
Electricity Market ◽  
Real Life ◽  
Optimization Approach ◽  
Case Scenario ◽  
Worst Case ◽  
Bidding Strategies ◽  
Wind Generators ◽  
Proposed Model ◽  
Optimal Bidding

In the recent electricity market framework, the profit of the generation companies depends on the decision of the operator on the schedule of its units, the energy price, and the optimal bidding strategies. Due to the expanded integration of uncertain renewable generators which is highly intermittent such as wind plants, the coordination with other facilities to mitigate the risks of imbalances is mandatory. Accordingly, coordination of wind generators with the evolutionary Electric Vehicles (EVs) is expected to boost the performance of the grid. In this paper, we propose a robust optimization approach for the coordination between the wind-thermal generators and the EVs in a virtual<br>power plant (VPP) environment. The objective of maximizing the profit of the VPP Operator (VPPO) is studied. The optimal bidding strategy of the VPPO in the day-ahead market under uncertainties of wind power, energy<br>prices, imbalance prices, and demand is obtained for the worst case scenario. A case study is conducted to assess the e?effectiveness of the proposed model in terms of the VPPO's profit. A comparison between the proposed model and the scenario-based optimization was introduced. Our results confirmed that, although the conservative behavior of the worst-case robust optimization model, it helps the decision maker from the fluctuations of the uncertain parameters involved in the production and bidding processes. In addition, robust optimization is a more tractable problem and does not suffer from<br>the high computation burden associated with scenario-based stochastic programming. This makes it more practical for real-life scenarios.<br>

Urban Transport

2018 ◽  
Author(s):  
José van
Keyword(s):  
Urban Areas ◽  
Urban Transport ◽  
Transport Sector ◽  
Public And Private ◽  
Transport Services ◽  
Ride Sharing ◽  
The World ◽  
Private And Public ◽  
Selection Mechanisms

Platformization affects the entire urban transport sector, effectively blurring the division between private and public transport modalities; existing public–private arrangements have started to shift as a result. This chapter analyzes and discusses the emergence of a platform ecology for urban transport, focusing on two central public values: the quality of urban transport and the organization of labor and workers’ rights. Using the prism of platform mechanisms, it analyzes how the sector of urban transport is changing societal organization in various urban areas across the world. Datafication has allowed numerous new actors to offer their bike-, car-, or ride-sharing services online; selection mechanisms help match old and new complementors with passengers. Similarly, new connective platforms are emerging, most prominently transport network companies such as Uber and Lyft that offer public and private transport options, as well as new platforms offering integrated transport services, often referred to as “mobility as a service.”

scholarly journals Robust neutrosophic programming approach for solving intuitionistic fuzzy multiobjective optimization problems

2021 ◽  
Author(s):  
Firoz Ahmad
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Practical Implication ◽  
Real Life ◽  
Future Research ◽  
Programming Approach ◽  
Solution Approach ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Multiobjective Optimization Problems

AbstractThis study presents the modeling of the multiobjective optimization problem in an intuitionistic fuzzy environment. The uncertain parameters are depicted as intuitionistic fuzzy numbers, and the crisp version is obtained using the ranking function method. Also, we have developed a novel interactive neutrosophic programming approach to solve multiobjective optimization problems. The proposed method involves neutral thoughts while making decisions. Furthermore, various sorts of membership functions are also depicted for the marginal evaluation of each objective simultaneously. The different numerical examples are presented to show the performances of the proposed solution approach. A case study of the cloud computing pricing problem is also addressed to reveal the real-life applications. The practical implication of the current study is also discussed efficiently. Finally, conclusions and future research scope are suggested based on the proposed work.

scholarly journals The Inventory Routing Problem with Demand Moves

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Annelieke C. Baller ◽  
Said Dabia ◽  
Guy Desaulniers ◽  
Wout E. H. Dullaert
Keyword(s):  
Urban Areas ◽  
Research Literature ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Solution Approach ◽  
Holding Cost ◽  
Inventory Holding Cost ◽  
Problem Instances ◽  
Inventory Holding

AbstractIn the Inventory Routing Problem, customer demand is satisfied from inventory which is replenished with capacitated vehicles. The objective is to minimize total routing and inventory holding cost over a time horizon. If the customers are located relatively close to each other, one has the opportunity to satisfy the demand of a customer by inventory stored at another nearby customer. In the optimization of the customer replenishments, this option can be included to lower total costs. This is for example the case for ATMs in urban areas where an ATM-user that wants to withdraw money could be redirected to another ATM. To the best of our knowledge, the possibility of redirecting end-users is new to the operations research literature and has not been implemented, but is being considered, in the industry. We formulate the Inventory Routing Problem with Demand Moves in which demand of a customer can (partially) be satisfied by the inventory of a nearby customer at a service cost depending on the quantity and the distance. We propose a branch-price-and-cut solution approach which is evaluated on problem instances from the literature. Cost improvements over the classical IRP of up to 10% are observed with average savings around 3%.

scholarly journals Building a Model of Integration of Urban Sharing and Public Transport Services

2021 ◽  
Vol 13 (6) ◽  
pp. 3086
Author(s):  
Marcin Jacek Kłos ◽  
Grzegorz Sierpiński
Keyword(s):  
Decision Making ◽  
Public Transport ◽  
Urban Transport ◽  
Extensive Literature ◽  
Transport Services ◽  
Harmful Emissions ◽  
Specific Factors ◽  
The Given ◽  
Public Transport Services ◽  
Potential Area

The intense growth of cities affects their inhabitants to a considerable extent. The issues facing the traveling population include congestion and growing harmful emissions. Urban transport requires changes towards eco-friendly solutions. However, even though new forms of traveling (sharing services) are being implemented, their integration with public transport remains problematic. On account of the large number of available services combined with the absence of their integration, city inhabitants are faced with the dilemma of choosing between one or several transport modes which would enable them to make the given trip. The main goal of this article is to propose a model for integration of different transport services which could support those who intend to travel in the decision-making process. Therefore, the parameters of a model of urban sharing services were identified and classified. The parameters discussed in the paper with reference to an extensive literature review describe how individual sharing services are functioning. What has also been identified is the location-specific factors as well as those related to the potential area of operation which affect the integration with public transport. In order to take all the relevant parameters into account and find a solution to the problem at hand, a multi-criteria decision-making approach has been proposed. To this end, scores and weights determining their impact on the model have been established. For purposes of the solution in question, the relevant calculations were conducted by referring to an actual need to travel between selected locations.

A mixed-integer optimization approach for homogeneous magnet design

TECHNOLOGY ◽  
2018 ◽  
Vol 06 (02) ◽  
pp. 49-58
Author(s):  
Iman Dayarian ◽  
Timothy C.Y. Chan ◽  
David Jaffray ◽  
Teo Stanescu
Keyword(s):  
Imaging Modality ◽  
Spatial Location ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Integer Optimization ◽  
Magnet Design ◽  
Field Homogeneity ◽  
Feasibility Constraints ◽  
Design Generation ◽  
Magnetic Resonance Imaging Mri

Magnetic resonance imaging (MRI) is a powerful diagnostic tool that has become the imaging modality of choice for soft-tissue visualization in radiation therapy. Emerging technologies aim to integrate MRI with a medical linear accelerator to form novel cancer therapy systems (MR-linac), but the design of these systems to date relies on heuristic procedures. This paper develops an exact, optimization-based approach for magnet design that 1) incorporates the most accurate physics calculations to date, 2) determines precisely the relative spatial location, size, and current magnitude of the magnetic coils, 3) guarantees field homogeneity inside the imaging volume, 4) produces configurations that satisfy, for the first time, small-footprint feasibility constraints required for MR-linacs. Our approach leverages modern mixed-integer programming (MIP), enabling significant flexibility in magnet design generation, e.g., controlling the number of coils and enforcing symmetry between magnet poles. Our numerical results demonstrate the superiority of our method versus current mainstream methods.

Interactive Evolution and Coordination of Urban Transport

2017 ◽  
Vol 42 (3) ◽  
pp. 20-24
Author(s):  
Yufang Jin ◽  
Xiangjian Zhang
Keyword(s):  
Urban System ◽  
Integrated System ◽  
Urban Transport ◽  
Transportation Infrastructure ◽  
Coordinated Development ◽  
Traffic Jam ◽  
Planning Strategy ◽  
Transport Services ◽  
The City ◽  
Economic Size

With the continuous expansion of urban scale, blindly increasing or controlling transportation infrastructure possibly creates a short board in an urban system. In this study, a macro traffic integrated system was constructed according to a city's economic size distribution and transportation infrastructure. The planning strategy of traffic, industry, space interaction and coordinated development was put forward. Through theoretical model, the evolution mechanism between transportation infrastructure and economic scale distribution was revealed. Starting from the center of the city and inter city level, China's new urbanization strategy was implemented, and a comprehensive transportation system model was built. The traffic planning in Singapore was taken as an example, and the solution to traffic problems such as congestion, traffic jam, and distance was obtained. Practice has proved that the rational and effective urban transportation infrastructure construction can effectively promote the coordinated development of economy and resources, and comprehensively enhance the level of integrated transport services.

An Integrated Design Optimization Approach for Quantitative and Qualitative Search Space

2003 ◽  
Author(s):  
Victor Oduguwa ◽  
Rajkumar Roy ◽  
Didier Farrugia
Keyword(s):  
Real World ◽  
Design Problem ◽  
Integrated Design ◽  
Search Space ◽  
Optimization Approach ◽  
Design Optimisation ◽  
Solution Approach ◽  
Rod Rolling ◽  
Algorithmic Engineering ◽  
Real World Problems

Most of the algorithmic engineering design optimisation approaches reported in the literature aims to find the best set of solutions within a quantitative (QT) search space of the given problem while ignoring related qualitative (QL) issues. These QL issues can be very important and by ignoring them in the optimisation search, can have expensive consequences especially for real world problems. This paper presents a new integrated design optimisation approach for QT and QL search space. The proposed solution approach is based on design of experiment methods and fuzzy logic principles for building the required QL models, and evolutionary multi-objective optimisation technique for solving the design problem. The proposed technique was applied to a two objectives rod rolling problem. The results obtained demonstrate that the proposed solution approach can be used to solve real world problems taking into account the related QL evaluation of the design problem.

scholarly journals Association rule hiding using integer linear programming

2021 ◽  
Vol 11 (4) ◽  
pp. 3451
Author(s):  
Suma B. ◽  
Shobha G.
Keyword(s):  
Data Mining ◽  
Linear Programming ◽  
Integer Linear Programming ◽  
Association Rule ◽  
Real Life ◽  
Linear Program ◽  
Integer Linear Program ◽  
Optimization Approach ◽  
Integer Linear Program Formulation ◽  
The Impact

<span>Privacy preserving data mining has become the focus of attention of government statistical agencies and database security research community who are concerned with preventing privacy disclosure during data mining. Repositories of large datasets include sensitive rules that need to be concealed from unauthorized access. Hence, association rule hiding emerged as one of the powerful techniques for hiding sensitive knowledge that exists in data before it is published. In this paper, we present a constraint-based optimization approach for hiding a set of sensitive association rules, using a well-structured integer linear program formulation. The proposed approach reduces the database sanitization problem to an instance of the integer linear programming problem. The solution of the integer linear program determines the transactions that need to be sanitized in order to conceal the sensitive rules while minimizing the impact of sanitization on the non-sensitive rules. We also present a heuristic sanitization algorithm that performs hiding by reducing the support or the confidence of the sensitive rules. The results of the experimental evaluation of the proposed approach on real-life datasets indicate the promising performance of the approach in terms of side effects on the original database.</span>

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