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Operations Research, Systems Engineering and Industrial Engineering Commons™
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- Optimization (8)
- Vehicle routing problem (6)
- Reinforcement learning (5)
- Ride-sourcing (3)
- Routing (3)
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- Vehicle routing (3)
- Analytical models (2)
- Autonomous agents (2)
- Electric Vehicle Routing Problem (2)
- Electric vehicles (2)
- Energy consumption (2)
- Genetic algorithm (2)
- Intelligent transportation systems (2)
- Mixed integer programming (2)
- Recursive logit (2)
- Shared mobility systems (2)
- Transportation (2)
- Urban areas (2)
- Urban consolidation center (2)
- Waterway transportation (2)
- Winner determination problem (2)
- Adaptive large neighborhood search (1)
- Agent application (1)
- Aircraft allocation (1)
- Airport ground handling (1)
- Ant colony algorithms (1)
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- Approximate dynamic programming (1)
- Approximate dynamic programming approach (1)
- Approximate value function (1)
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Articles 31 - 60 of 70
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
A Genetic Algorithm To Minimise Number Of Vehicles In An Electric Vehicle Routing Problem, Kiian Leong Bertran Queck, Hoong Chuin Lau
A Genetic Algorithm To Minimise Number Of Vehicles In An Electric Vehicle Routing Problem, Kiian Leong Bertran Queck, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Electric Vehicles (EVs) and charging infrastructure are starting to become commonplace in major cities around the world. For logistics providers to adopt an EV fleet, there are many factors up for consideration, such as route planning for EVs with limited travel range as well as long-term planning of fleet size. In this paper, we present a genetic algorithm to perform route planning that minimises the number of vehicles required. Specifically, we discuss the challenges on the violations of constraints in the EV routing problem (EVRP) arising from applying genetic algorithm operators. To overcome the challenges, techniques specific to addressing the …
Bus Frequency Optimization: When Waiting Time Matters In User Satisfaction, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng
Bus Frequency Optimization: When Waiting Time Matters In User Satisfaction, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng
Research Collection School Of Computing and Information Systems
Reorganizing bus frequency to cater for the actual travel demand can save the cost of the public transport system significantly. Many, if not all, existing studies formulate this as a bus frequency optimization problem which tries to minimize passengers’ average waiting time. However, many investigations have confirmed that the user satisfaction drops faster as the waiting time increases. Consequently, this paper studies the bus frequency optimization problem considering the user satisfaction. Specifically, for the first time to our best knowledge, we study how to schedule the buses such that the total number of passengers who could receive their bus services …
Goods Consumed During Transit In Split Delivery Vehicle Routing Problems: Modeling And Solution, Wenzhe Yang, Di Wang, Wei Pang, Ah-Hwee Tan, You Zhou
Goods Consumed During Transit In Split Delivery Vehicle Routing Problems: Modeling And Solution, Wenzhe Yang, Di Wang, Wei Pang, Ah-Hwee Tan, You Zhou
Research Collection School Of Computing and Information Systems
This article presents the modeling and solution of an extended type of split delivery vehicle routing problem (SDVRP). In SDVRP, the demands of customers need to be met by efficiently routing a given number of capacitated vehicles, wherein each customer may be served multiple times by more than one vehicle. Furthermore, in many real-world scenarios, consumption of vehicles en route is the same as the goods being delivered to customers, such as food, water and fuel in rescue or replenishment missions in harsh environments. Moreover, the consumption may also be in virtual forms, such as time spent in constrained tasks. …
Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Increasing global maritime traffic coupled with rapid digitization and automation in shipping mandate developing next generation maritime traffic management systems to mitigate congestion, increase safety of navigation, and avoid collisions in busy and geographically constrained ports (such as Singapore's). To achieve these objectives, we model the maritime traffic as a large multiagent system with individual vessels as agents, and VTS (Vessel Traffic Service) authority as a regulatory agent. We develop a hierarchical reinforcement learning approach where vessels first select a high level action based on the underlying traffic flow, and then select the low level action that determines their future …
Route Choice Behaviour And Travel Information In A Congested Network: Static And Dynamic Recursive Models, Giselle De Moraes Ramos, Tien Mai, Winnie Daamen, Emma Frejinger
Route Choice Behaviour And Travel Information In A Congested Network: Static And Dynamic Recursive Models, Giselle De Moraes Ramos, Tien Mai, Winnie Daamen, Emma Frejinger
Research Collection School Of Computing and Information Systems
Travel information has the potential to influence travellers choices, in order to steer travellers to less congested routes and alleviate congestion. This paper investigates, on the one hand, how travel information affects route choice behaviour, and on the other hand, the impact of the travel time representation on the interpretation of parameter estimates and prediction accuracy. To this end, we estimate recursive models using data from an innovative data collection effort consisting of route choice observation data from GPS trackers, travel diaries and link travel times on the overall network. Though such combined data sets exist, these have not yet …
Incorporating A Reverse Logistics Scheme In A Vehicle Routing Problem With Cross-Docking Network: A Modelling Approach, Audrey Tedja Widjaja, Aldy Gunawan, Panca Jodiawan, Vincent F. Yu
Incorporating A Reverse Logistics Scheme In A Vehicle Routing Problem With Cross-Docking Network: A Modelling Approach, Audrey Tedja Widjaja, Aldy Gunawan, Panca Jodiawan, Vincent F. Yu
Research Collection School Of Computing and Information Systems
Reverse logistics has been implemented by various companies because of its ability to gain more profit and maintain the competitiveness of the company. However, extensive studies on the vehicle routing problem with cross-docking (VRPCD) only considered the forward flow instead of the reverse flow. Motivated by the ability of a VRPCD network to minimize the distribution cost in the forward flow, this research incorporates the reverse logistics scheme in a VRPCD network, namely the VRP with reverse cross-docking (VRP-RCD). We propose a VRP-RCD mathematical model for a four-level supply chain network that involves suppliers, cross-dock, customers, and outlets. The main …
Neural Approximate Dynamic Programming For On-Demand Ride-Pooling, Sanket Shah, Meghna Lowalekar, Pradeep Varakantham
Neural Approximate Dynamic Programming For On-Demand Ride-Pooling, Sanket Shah, Meghna Lowalekar, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
On-demand ride-pooling (e.g., UberPool, LyftLine, GrabShare) has recently become popular because of its ability to lower costs for passengers while simultaneously increasing revenue for drivers and aggregation companies (e.g., Uber). Unlike in Taxi on Demand (ToD) services – where a vehicle is assigned one passenger at a time – in on-demand ride-pooling, each vehicle must simultaneously serve multiple passengers with heterogeneous origin and destination pairs without violating any quality constraints. To ensure near real-time response, existing solutions to the real-time ride-pooling problem are myopic in that they optimise the objective (e.g., maximise the number of passengers served) for the current …
A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja
A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja
Research Collection School Of Computing and Information Systems
A green mixed fleet vehicle routing with realistic energy consumption and partial recharges problem (GMFVRP-REC-PR) is addressed in this paper. This problem involves a fixed number of electric vehicles and internal combustion vehicles to serve a set of customers. The realistic energy consumption which depends on several variables is utilized to calculate the electricity consumption of an electric vehicle and fuel consumption of an internal combustion vehicle. Partial recharging policy is included into the problem to represent the real life scenario. The objective of this problem is to minimize the total travelled distance and the total emission produced by internal …
Model And Analysis Of Labor Supply For Ride-Sharing Platforms In The Presence Of Sample Self-Selection And Endogeneity, Hao Sun, Hai Wang, Zhixi Wan
Model And Analysis Of Labor Supply For Ride-Sharing Platforms In The Presence Of Sample Self-Selection And Endogeneity, Hao Sun, Hai Wang, Zhixi Wan
Research Collection School Of Computing and Information Systems
With the popularization of ride-sharing services, drivers working as freelancers on ride-sharing platforms can design their schedules flexibly. They make daily decisions regard- ing whether to participate in work, and if so, how many hours to work. Factors such as hourly income rate affect both the participation decision and working-hour decision, and evaluation of the impacts of hourly income rate on labor supply becomes important. In this paper, we propose an econometric framework with closed-form measures to estimate both the participation elasticity (i.e., extensive margin elasticity) and working-hour elasticity (i.e., intensive margin elasticity) of labor supply. We model the sample …
Zac: A Zone Path Construction Approach For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Zac: A Zone Path Construction Approach For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Real-time ridesharing systems such as UberPool, Lyft Line, GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and reduce traffic on the roads by grouping customers with similar itineraries. The key challenge in these systems is to group the right requests to travel in available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. The most relevant existing work has focussed on generating as many relevant feasible (with respect to available delay for customers) combinations of requests (referred to as trips) as possible in real-time. …
Re-Org: An Online Repositioning Guidance Agent, Muralidhar Konda, Pradeep Varakantham, Aayush Saxena, Meghna Lowalekar
Re-Org: An Online Repositioning Guidance Agent, Muralidhar Konda, Pradeep Varakantham, Aayush Saxena, Meghna Lowalekar
Research Collection School Of Computing and Information Systems
No abstract provided.
Route Planning For A Fleet Of Electric Vehicles With Waiting Times At Charging Stations, Baoxiang Li, Shashi Shekhar Jha, Hoong Chuin Lau
Route Planning For A Fleet Of Electric Vehicles With Waiting Times At Charging Stations, Baoxiang Li, Shashi Shekhar Jha, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Electric Vehicles (EVs) are the next wave of technology in the transportation industry. EVs are increasingly becoming common for personal transport and pushing the boundaries to become the mainstream mode of transportation. Use of such EVs in logistic fleets for delivering customer goods is not far from becoming reality. However, managing such fleet of EVs bring new challenges in terms of battery capacities and charging infrastructure for efficient route planning. Researchers have addressed such issues considering different aspects of the EVs such as linear battery charging/discharging rate, fixed travel times, etc. In this paper, we address the issue of waiting …
Routing And Scheduling For A Last-Mile Transportation System, Hai Wang
Routing And Scheduling For A Last-Mile Transportation System, Hai Wang
Research Collection School Of Computing and Information Systems
The last-mile problem concerns the provision of travel services from the nearest public transportation node to a passenger’s home or other destination. We study the operation of an emerging last-mile transportation system (LMTS) with batch demands that result from the arrival of groups of passengers who desire last-mile service at urban metro stations or bus stops. Routes and schedules are determined for a multivehicle fleet of delivery vehicles, with the objective of minimizing passenger waiting time and riding time. An exact mixed-integer programming (MIP) model for LMTS operations is presented first, which is difficult to solve optimally within acceptable computational …
Analysis Of Bus Ride Comfort Using Smartphone Sensor Data, Hoong-Chor Chin, Xingting Pang, Zhaoxia Wang
Analysis Of Bus Ride Comfort Using Smartphone Sensor Data, Hoong-Chor Chin, Xingting Pang, Zhaoxia Wang
Research Collection School Of Computing and Information Systems
Passenger comfort is an important indicator that is often used to measure the quality of public transport services. It may also be a crucial factor in the passenger’s choice of transport mode. The typical method of assessing passenger comfort is through a passenger interview survey which can be tedious. This study aims to investigate the relationship between bus ride comfort based on ride smoothness and the vehicle’s motion detected by the smartphone sensors. An experiment was carried out on a bus fixed route within the University campus where comfort levels were rated on a 3-point scale and recorded at 5-second …
A State Aggregation Approach For Stochastic Multiperiod Last-Mile Ride-Sharing Problems, Lucas Agussurja, Shih-Fen Cheng, Hoong Chuin Lau
A State Aggregation Approach For Stochastic Multiperiod Last-Mile Ride-Sharing Problems, Lucas Agussurja, Shih-Fen Cheng, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
The arrangement of last-mile services is playing an increasingly important role in making public transport more accessible. We study the use of ridesharing in satisfying last-mile demands with the assumption that demands are uncertain and come in batches. The most important contribution of our paper is a two-level Markov decision process framework that is capable of generating a vehicle-dispatching policy for the aforementioned service. We introduce state summarization, representative states, and sample-based cost estimation as major approximation techniques in making our approach scalable. We show that our approach converges and solution quality improves as sample size increases. We also apply …
Design And Implementation Of Decision Support For Traffic Management At Multipurpose Port Gates, Ketki Kulkarni, Hoong Chuin Lau, Hai Wang, Sathyavarathan Sivabalasingam, Trong Khiem Tran
Design And Implementation Of Decision Support For Traffic Management At Multipurpose Port Gates, Ketki Kulkarni, Hoong Chuin Lau, Hai Wang, Sathyavarathan Sivabalasingam, Trong Khiem Tran
Research Collection School Of Computing and Information Systems
Effective traffic management can help port operators gain a competitive edge in service level and efficient use of limited resources. One critical aspect of traffic management is gate operations management, ensuring a good customer experience to logistic carriers and considering the impact of congestion in and around the port. In this paper, we describe the design and implementation of a decision support tool to help gate operators plan for future scenarios with fluctuating demand and limited resources. We propose a simulation optimization framework which incorporates theoretical results from queuing theory to approximate complex multi-lane multi-server systems. Our major contribution in …
Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye
Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye
Research Collection School Of Computing and Information Systems
Surge pricing is commonly used in on-demand ride-sourcing platforms (e.g., Uber, Lyft and Didi) to dynamically balance demand and supply. However, since the price for ride service cannot be unlimited, there is usually a reasonable or legitimate range of prices in practice. Such a constrained surge pricing strategy fails to balance demand and supply in certain cases, e.g., even adopting the maximum allowed price cannot reduce the demand to an affordable level during peak hours. In addition, the practice of surge pricing is controversial and has stimulated long debate regarding its pros and cons. To address the limitation of current …
Bounded Rank Optimization For Effective And Efficient Emergency Response, Pallavi Madhusudan Manohar, Pradeep Varakantham, Hoong Chuin Lau
Bounded Rank Optimization For Effective And Efficient Emergency Response, Pallavi Madhusudan Manohar, Pradeep Varakantham, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Effective placement of emergency response vehicles (such as ambulances, fire trucks, police cars) to deal with medical, fire or criminal activities can reduce the incident response time by few seconds, which in turn can potentially save a human life. Owing to its adoption in Emergency Medical Services (EMSs) worldwide, existing research on improving emergency response has focused on optimizing the objective of bounded time (i.e. number of incidents served in a fixed time). Due to the dependence of this objective on temporal uncertainty, optimizing the bounded time objective is challenging. In this paper, we propose a new objective referred to …
Resource-Constrained Scheduling For Maritime Traffic Management, Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau
Resource-Constrained Scheduling For Maritime Traffic Management, Lucas Agussurja, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We address the problem of mitigating congestion and preventing hotspots in busy water areas such as Singapore Straits and port waters. Increasing maritime traffic coupled with narrow waterways makes vessel schedule coordination for just-in-time arrival critical for navigational safety. Our contributions are: 1) We formulate the maritime traffic management problem based on the real case study of Singapore waters; 2) We model the problem as a variant of the resource-constrained project scheduling problem (RCPSP), and formulate mixed-integer and constraint programming (MIP/CP) formulations; 3) To improve the scalability, we develop a combinatorial Benders (CB) approach that is significantly more effective than …
A Multiagent-Based Approach For Vehicle Routing By Considering Both Arriving On Time And Total Travel Time, Zhiguang Cao, Hongliang Guo, Jie Zhang
A Multiagent-Based Approach For Vehicle Routing By Considering Both Arriving On Time And Total Travel Time, Zhiguang Cao, Hongliang Guo, Jie Zhang
Research Collection School Of Computing and Information Systems
Arriving on time and total travel time are two important properties for vehicle routing. Existing route guidance approaches always consider them independently, because they may conflict with each other. In this article, we develop a semi-decentralized multiagent-based vehicle routing approach where vehicle agents follow the local route guidance by infrastructure agents at each intersection, and infrastructure agents perform the route guidance by solving a route assignment problem. It integrates the two properties by expressing them as two objective terms of the route assignment problem. Regarding arriving on time, it is formulated based on the probability tail model, which aims to …
Efficient Gate System Operations For A Multipurpose Port Using Simulation Optimization, Ketki Kulkarni, Trong Khiem Tran, Hai Wang, Hoong Chuin Lau
Efficient Gate System Operations For A Multipurpose Port Using Simulation Optimization, Ketki Kulkarni, Trong Khiem Tran, Hai Wang, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Port capacity is determined by three major infrastructural resources namely, berths, yards and gates. Theadvertised capacity is constrained by the least of the capacities of the three resources. While a lot ofattention has been paid to optimizing berth and yard capacities, not much attention has been given toanalyzing the gate capacity. The gates are a key node between the land-side and sea-side operations in anocean-to-cities value chain. The gate system under consideration, located at an important port in an Asiancity, is a multi-class parallel queuing system with non-homogeneous Poisson arrivals. It is hard to obtaina closed form analytic approach for …
Combinatorial Auction For Transportation Matching Service: Formulation And Adaptive Large Neighborhood Search Heuristic, Baoxiang Li, Hoong Chuin Lau
Combinatorial Auction For Transportation Matching Service: Formulation And Adaptive Large Neighborhood Search Heuristic, Baoxiang Li, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
This paper considers the problem of matching multiple shippers and multi-transporters for pickups and drop-offs, where the goal is to select a subset of group jobs (shipper bids) that maximizes profit. This is the underlying winner determination problem in an online auction-based vehicle sharing platform that matches transportation demand and supply, particularly in a B2B last-mile setting. Each shipper bid contains multiple jobs, and each job has a weight, volume, pickup location, delivery location and time window. On the other hand, each transporter bid specifies the vehicle capacity, available time periods, and a cost structure. This double-sided auction will be …
A Multi-Agent System For Coordinating Vessel Traffic, Teck-Hou Teng, Hoong Chuin Lau, Akshat Kumar
A Multi-Agent System For Coordinating Vessel Traffic, Teck-Hou Teng, Hoong Chuin Lau, Akshat Kumar
Research Collection School Of Computing and Information Systems
Environmental, regulatory and resource constraints affects the safety and efficiency of vessels navigating in and out of the ports. Movement of vessels under such constraints must be coordinated for improving safety and efficiency. Thus, we frame the vessel coordination problem as a multi-agent path-finding (MAPF) problem. We solve this MAPF problem using a Coordinated Path-Finding (CPF) algorithm. Based on the local search paradigm, the CPF algorithm improves on the aggregated path quality of the vessels iteratively. Outputs of the CPF algorithm are the coordinated trajectories. The Vessel Coordination Module (VCM) described here is the module encapsulating our MAPF-based approach for …
Dynamic Repositioning To Reduce Lost Demand In Bike Sharing Systems, Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet
Dynamic Repositioning To Reduce Lost Demand In Bike Sharing Systems, Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Bike Sharing Systems (BSSs) are widely adopted in major cities of the world due to concerns associated with extensive private vehicle usage, namely, increased carbon emissions, traffic congestion and usage of nonrenewable resources. In a BSS, base stations are strategically placed throughout a city and each station is stocked with a pre-determined number of bikes at the beginning of the day. Customers hire the bikes from one station and return them at another station. Due to unpredictable movements of customers hiring bikes, there is either congestion (more than required) or starvation (fewer than required) of bikes at base stations. Existing …
Traffic Simulation Model For Port Planning And Congestion Prevention, Baoxiang Li, Kar Way Tan, Trong Khiem Tran
Traffic Simulation Model For Port Planning And Congestion Prevention, Baoxiang Li, Kar Way Tan, Trong Khiem Tran
Research Collection School Of Computing and Information Systems
Effective management of land-side transportation provides the competitive advantage to port terminal operators in improving services and efficient use of limited space in an urban port. We present a hybrid simulation model that combines traffic-flow modeling and discrete-event simulation for land-side port planning and evaluation of traffic conditions for a number of what-if scenarios. We design our model based on a real-world case of a bulk cargo port. The problem is interesting due to complexity of heterogeneous closed-looped internal vehicles and external vehicles traveling in spaces with very limited traffic regulation (no traffic lights, no traffic wardens) and the traffic …
Improving Carbon Efficiency Through Container Size Optimization And Shipment Consolidation, Nang Laik Ma, Kar Way Tan, Edwin Lik Ming Chong
Improving Carbon Efficiency Through Container Size Optimization And Shipment Consolidation, Nang Laik Ma, Kar Way Tan, Edwin Lik Ming Chong
Research Collection School Of Computing and Information Systems
Purpose: Many manufacturing companies that ship goods through full container loads found themselves under-utilizing the containers and resulting in higher carbon footprint per volume shipment. One of the reasons is the choice of non-ideal container sizes for their shipments. Consolidation fills up the containers more efficiently that reduces the overall carbon footprint. The objective of this paper is to support decisions on selection of appropriate combination of container sizes and shipment consolidation for a manufacturing company. We develop two-steps model which first takes the volumes to be shipped as an input and provide the combination of container sizes required; then …
Designing Bus Transit Services For Routine Crowd Situations At Large Event Venues, Jianli Du, Shih-Fen Cheng, Hoong Chuin Lau
Designing Bus Transit Services For Routine Crowd Situations At Large Event Venues, Jianli Du, Shih-Fen Cheng, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We are concerned with the routine crowd management problem after a major event at a known venue. Without properly design complementary transport services, such sudden crowd build-ups will overwhelm the existing infrastructure. In this paper, we introduce a novel flow-rate based model to model the dynamic movement of passengers over the transportation flow network. Based on this basic model, an integer linear programming model is proposed to solve the bus transit problem permanently. We validate our model against a real scenario in Singapore, where a newly constructed mega-stadium hosts various large events regularly. The results show that the proposed approach …
A Rolling Horizon Auction Mechanism And Virtual Pricing Of Shipping Capacity For Urban Consolidation Centers, Chen Wang, Hoong Chuin Lau, Yun Fong Lim
A Rolling Horizon Auction Mechanism And Virtual Pricing Of Shipping Capacity For Urban Consolidation Centers, Chen Wang, Hoong Chuin Lau, Yun Fong Lim
Research Collection School Of Computing and Information Systems
A number of cities around the world have adopted urban consolidation centers (UCCs) to address challenges of last-mile deliveries. At the UCC, goods are consolidated based on their destinations prior to their deliveries into city centers. Typically, a UCC owns a fleet of ecofriendly vehicles to carry out such deliveries. Shippers/carriers that make use of the UCC’s service hence no longer need to be restricted by timewindow and vehicle-type regulations. As a result, they retain the ability to deploy large trucks for the economies of scale from the source to the UCC which is located outside the city center. Furthermore, …
Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan
Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan
Research Collection School Of Computing and Information Systems
Profitable tour problem (PTP) belongs to the class of vehicle routing problem (VRP) with profits seeking to maximize the difference between the total collected profit and the total cost incurred. Traditionally, PTP involves single vehicle. In this paper, we consider PTP with multiple vehicles. Unlike the classical VRP that seeks to serve all customers, PTP involves the strategic-level customer selection so as to maximize the total collected profit and the operational-level route optimization to minimize the total cost incurred. Therefore, PTP is essentially the knapsack problem at the strategic level with VRP at the operational level. That means the evolutionary …
Scalable Randomized Patrolling For Securing Rapid Transit Networks, Pradeep Varakantham, Hoong Chuin Lau, Zhi Yuan
Scalable Randomized Patrolling For Securing Rapid Transit Networks, Pradeep Varakantham, Hoong Chuin Lau, Zhi Yuan
Research Collection School Of Computing and Information Systems
Mass Rapid Transit using rail is a popular mode of transport employed by millions of people in many urban cities across the world. Typically, these networks are massive, used by many and thus, can be a soft target for criminals. In this paper, we consider the problem of scheduling randomised patrols for improving security of such rail networks. Similar to existing work in randomised patrols for protecting critical infrastructure, we also employ Stackelberg Games to represent the problem. In solving the Stackelberg games for massive rail networks, we make two key contributions. Firstly, we provide an approach called RaPtoR for …