Digital Commons Network^™

Dynamic Scheduling With Uncertain Job Types, Zuo-Jun Max Shen, Jingui Xie, Zhichao Zheng, Han Zhou

Research Collection Lee Kong Chian School Of Business

Uncertain job types can arise as a result of predictive or diagnostic inaccuracy in healthcare or repair service systems and unknown preferences in matching service systems. In this paper, we study systems with multiple types of jobs, in which type information is imperfect and will be updated dynamically. Each job has a prior probability of belonging to a certain type which may be predicted by data, models, or experts. A job can only be processed by the right machine, and a job assigned to the wrong machine must be rescheduled. More information is learned from the mismatch, and job type …

A Data-Driven Approach For Scheduling Bus Services Subject To Demand Constraints, Brahmanage Janaka Chathuranga Thilakarathna, Thivya Kandappu, Baihua Zheng

Research Collection School Of Computing and Information Systems

Passenger satisfaction is extremely important for the success of a public transportation system. Many studies have shown that passenger satisfaction strongly depends on the time they have to wait at the bus stop (waiting time) to get on a bus. To be specific, user satisfaction drops faster as the waiting time increases. Therefore, service providers want to provide a bus to the waiting passengers within a threshold to keep them satisfied. It is a two-pronged problem: (a) to satisfy more passengers the transport planner may increase the frequency of the buses, and (b) in turn, the increased frequency may impact …

The Investment Chapter In The Regional Comprehensive Economic Partnership: Enhanced Rules Without Enforcement Mechanism, Henry S. Gao

Research Collection Yong Pung How School Of Law

This Chapter examines the legal rules in the investment chapter in the Regional Comprehensive Economic Partnership (RCEP). It starts with an overview and summary of the main provisions in the chapter, followed by an assessment of the rules by comparing established free trade agreements (FTAs), especially the Comprehensive and Progressive Trans-Pacific Partnership. In particular, it notes that the chapter, whilst largely following the established approaches to investment in other FTAs, also includes important twists to the common rules to favour the host states. The last part discusses the conspicuous absence of an investor-state dispute settlement mechanism, its pros and cons, …

Reinforcement Learning Approach To Solve Dynamic Bi-Objective Police Patrol Dispatching And Rescheduling Problem, Waldy Joe, Hoong Chuin Lau, Jonathan Pan

Research Collection School Of Computing and Information Systems

Police patrol aims to fulfill two main objectives namely to project presence and to respond to incidents in a timely manner. Incidents happen dynamically and can disrupt the initially-planned patrol schedules. The key decisions to be made will be which patrol agent to be dispatched to respond to an incident and subsequently how to adapt the patrol schedules in response to such dynamically-occurring incidents whilst still fulfilling both objectives; which sometimes can be conflicting. In this paper, we define this real-world problem as a Dynamic Bi-Objective Police Patrol Dispatching and Rescheduling Problem and propose a solution approach that combines Deep …

Hybrid Tabu Search Algorithm For Unrelated Parallel Machine Scheduling In Semiconductor Fabs With Setup Times, Job Release, And Expired Times, Changyu Chen, Madhi Fathi, Marzieh Khakifirooz, Kan Wu

Research Collection School Of Computing and Information Systems

This research is motivated by a scheduling problem arising in the ion implantation process of wafer fabrication. The ion implementation scheduling problem is modeled as an unrelated parallel machine scheduling (UPMS) problem with sequence-dependent setup times that are subject to job release time and expiration time of allowing a job to be processed on a specific machine, defined as: R|rj,eij,STsd|Cmax. The objective is first to maximize the number of processed jobs, then minimize the maximum completion time (makespan), and finally minimize the maximum completion times of the non-bottleneck machines. A mixed-integer programming (MIP) model is proposed as a solution approach …

Limousine Service Management: Capacity Planning With Predictive Analytics And Optimization, Peng Liu, Ying Chen, Chung-Piaw Teo

Research Collection Lee Kong Chian School Of Business

The limousine service in luxury hotels is an integral component of the whole customer journey in the hospitality industry. One of the largest hotels in Singapore manages a fleet of both in-house and outsourced vehicles around the clock, serving 9,000 trips per month on average. The need for vehicles may scale up rapidly, especially during special events and festive periods in the country. The excess demand is met by having additional outsourced vehicles on standby, incurring millions of dollars of additional expenses per year for the hotel. Determining the required number of limousines by hour of the day is a …

A Matheuristic Algorithm For The Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu

Research Collection School Of Computing and Information Systems

This paper studies the integration of the vehicle routing problem with cross-docking (VRPCD). The aim is to find a set of routes to deliver products from a set of suppliers to a set of customers through a cross-dock facility, such that the operational and transportation costs are minimized, without violating the vehicle capacity and time horizon constraints. A two-phase matheuristic based on column generation is proposed. The first phase focuses on generating a set of feasible candidate routes in both pickup and delivery processes by implementing an adaptive large neighborhood search algorithm. A set of destroy and repair operators are …

Reinforcement Learning For Zone Based Multiagent Pathfinding Under Uncertainty, Jiajing Ling, Tarun Gupta, Akshat Kumar

Research Collection School Of Computing and Information Systems

We address the problem of multiple agents finding their paths from respective sources to destination nodes in a graph (also called MAPF). Most existing approaches assume that all agents move at fixed speed, and that a single node accommodates only a single agent. Motivated by the emerging applications of autonomous vehicles such as drone traffic management, we present zone-based path finding (or ZBPF) where agents move among zones, and agents' movements require uncertain travel time. Furthermore, each zone can accommodate multiple agents (as per its capacity). We also develop a simulator for ZBPF which provides a clean interface from the …

Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh

Research Collection School Of Computing and Information Systems

Traffic congestion reduces productivity of individuals by increasing time spent in traffic and also increases pollution. To reduce traffic congestion by better handling dynamic traffic patterns, recent work has focused on online traffic signal control. Typically, the objective in traffic signal control is to minimize expected delay over all vehicles given the uncertainty associated with the vehicle turn movements at intersections. In order to ensure responsiveness in decision making, a typical approach is to compute a schedule that minimizes the delay for the expected scenario of vehicle movements instead of minimizing expected delay over the feasible vehicle movement scenarios. Such …

Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu

Research Collection School Of Computing and Information Systems

Cross-docking is considered as a method to manage and control the inventory flow, which is essential in the context of supply chain management. This paper studies the integration of the vehicle routing problem with cross-docking, namely VRPCD which has been extensively studied due to its ability to reducethe overall costs occurring in a supply chain network. Given a fleet of homogeneous vehicles for delivering a single type of product from suppliers to customers through a cross-dock facility, the objective of VRPCD is to determine the number of vehicles used and the corresponding vehicle routes, such that the vehicleoperational and transportation …

A Matheuristic Algorithm For Solving The Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu

Research Collection School Of Computing and Information Systems

This paper studies the integration of the vehicle routing problem with cross-docking, namely VRPCD. The aim is to find a set of routes to deliver single products from a set of suppliers to a set of customers through a cross-dock facility, such that the operational and transportation costs are minimized, without violating the vehicle capacity and time horizon constraints. A two-phase matheuristic approach that uses the routes of the local optima of an adaptive large neighborhood search (ALNS) as columns in a set-partitioning formulation of the VRPCD is designed. This matheuristic outperforms the state-of-the-art algorithms in solving a subset of …

Mechanism Design For Strategic Project Scheduling, Pradeep Varakantham, Na Fu

Research Collection School Of Computing and Information Systems

Organizing large scale projects (e.g., Conferences, IT Shows, F1 race) requires precise scheduling of multiple dependent tasks on common resources where multiple selfish entities are competing to execute the individual tasks. In this paper, we consider a well studied and rich scheduling model referred to as RCPSP (Resource Constrained Project Scheduling Problem). The key change to this model that we consider in this paper is the presence of selfish entities competing to perform individual tasks with the aim of maximizing their own utility. Due to the selfish entities in play, the goal of the scheduling problem is no longer only …

Augmenting Decisions Of Taxi Drivers Through Reinforcement Learning For Improving Revenues, Tanvi Verma, Pradeep Varakantham, Sarit Kraus, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Taxis (which include cars working with car aggregation systems such as Uber, Grab, Lyft etc.) have become a critical component in the urban transportation. While most research and applications in the context of taxis have focused on improving performance from a customer perspective, in this paper,we focus on improving performance from a taxi driver perspective. Higher revenues for taxi drivers can help bring more drivers into the system thereby improving availability for customers in dense urban cities.Typically, when there is no customer on board, taxi driverswill cruise around to find customers either directly (on thestreet) or indirectly (due to a …

Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

Duplicate record, see https://ink.library.smu.edu.sg/sis_research/3271. The Orienteering Problem (OP) has received a lot of attention in the past few decades. The OP is a routing problem in which the goal is to determine a subset of nodes to visit, and in which order, so that the total collected score is maximized and a given time budget is not exceeded. A number of typical variants has been studied, such as the Team OP, the (Team) OP with Time Windows and the Time Dependent OP. Recently, a number of new variants of the OP was introduced, such as the Stochastic OP, the …

Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen

Research Collection School Of Computing and Information Systems

The Orienteering Problem (OP) has received a lot of attention in the past few decades. The OP is a routing problem in which the goal is to determine a subset of nodes to visit, and in which order, so that the total collected score is maximized and a given time budget is not exceeded. A number of typical variants has been studied, such as the Team OP, the (Team) OP with Time Windows and the Time Dependent OP. Recently, a number of new variants of the OP was introduced, such as the Stochastic OP, the Generalized OP, the Arc OP, …

Strategic Planning For Setting Up Base Stations In Emergency Medical Systems, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Emergency Medical Systems (EMSs) are an important component of public health-care services. Improving infrastructure for EMS and specifically the construction of base stations at the ”right” locations to reduce response times is the main focus of this paper. This is a computationally challenging task because of the: (a) exponentially large action space arising from having to consider combinations of potential base locations, which themselves can be significant; and (b) direct impact on the performance of the ambulance allocation problem, where we decide allocation of ambulances to bases. We present an incremental greedy approach to discover the placement of bases that …

Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Decentralized POMDP is an expressive model for multi-agent planning. Finite-state controllers (FSCs)---often used to represent policies for infinite-horizon problems---offer a compact, simple-to-execute policy representation. We exploit novel connections between optimizing decentralized FSCs and the dual linear program for MDPs. Consequently, we describe a dual mixed integer linear program (MIP) for optimizing deterministic FSCs. We exploit the Dec-POMDP structure to devise a compact MIP and formulate constraints that result in policies executable in partially-observable decentralized settings. We show analytically that the dual formulation can also be exploited within the expectation maximization (EM) framework to optimize stochastic FSCs. The resulting EM algorithm …

Ad Revenue Optimization In Live Broadcasting, Dana G. Popescu, Pascale Crama

Research Collection Lee Kong Chian School Of Business

In live broadcasting, the break lengths available for commercials are not always fixed and known in advance (e.g., strategic and injury time-outs are of variable duration in live sports transmissions). Broadcasters actively manage their advertising revenue by jointly optimizing sales and scheduling policies. We characterize the optimal dynamic schedule in a simplified setting that incorporates stochastic break durations and advertisement lengths of 15 and 30 seconds. The optimal policy is a "greedy" look-ahead rule that accounts for the remaining number of breaks; in this setting, there is no value to perfect information at the scheduling stage, and hence knowing the …

Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We study a real-world problem arising from the operations of a hospital service provider, which we term the master physician scheduling problem. It is a planning problem of assigning physicians’ full range of day-to-day duties (including surgery, clinics, scopes, calls, administration) to the defined time slots/shifts over a time horizon, incorporating a large number of constraints and complex physician preferences. The goals are to satisfy as many physicians’ preferences and duty requirements as possible while ensuring optimum usage of available resources. We propose mathematical programming models that represent different variants of this problem. The models were tested on a real …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Finding Robust-Under-Risk Solutions For Flowshop Scheduling, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We propose and explore, in the context of benchmark problems for flowshop scheduling, a risk-based concept of robustness for optimization problems. This risk-based concept is in distinction to, and complements, the uncertainty-based concept employed in the field known as robust optimization. Implementation of our concept requires problem solution methods that sample the solution space intelligently and that produce large numbers of distinct sample points. With these solutions to hand, their robustness scores are easily obtained and heuristically robust solutions found. We find evolutionary computation to be effective for this purpose on these problems.

Optimal Advertisement Scheduling In Breaks Of Random Lengths, Ajay Srinivasan Aravamudhan

Dissertations and Theses Collection (Open Access)

Broadcasters generate a large part of their revenue through advertising, especially in live sports. Scheduling advertisements can be challenging in live broadcasting, however, for sports such as Cricket that have breaks of random lengths and number during which the ads are shown. This uncertainty, coupled with the high price of spots for major competitions, means that improving ad scheduling can add significant value to the broadcaster. This problem shares similarities with the stochastic cutting stock problem and the dynamic stochastic knapsack problem, with applications in the wood, steel and paper industry and the transportation industry respectively.

This dissertation adds to …

Decentralized Resource Allocation And Scheduling Via Walrasian Auctions With Negotiable Agents, Huaxing Chen, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

This paper is concerned with solving decentralized resource allocation and scheduling problems via auctions with negotiable agents by allowing agents to switch their bid generation strategies within the auction process, such that a better system wide performance is achieved on average as compared to the conventional walrasian auction running with agents of fixed bid generation strategy. We propose a negotiation mechanism embedded in auctioneer to solicit bidders’ change of strategies in the process of auction. Finally we benchmark our approach against conventional auctions subject to the real-time large-scale dynamic resource coordination problem to demonstrate the effectiveness of our approach.

Dynamic Allocation Of Airline Check-In Counters: A Queueing Optimisation Approach, Mahmut Parlar, Sharafali Moosa

Research Collection Lee Kong Chian School Of Business

This paper was motivated by an observation in an international airport with regard to allocation of resources for check-in counters. In an exclusive check-in counter system, each flight has a dedicated number of counters that will be open until at least a half-hour before the scheduled departure of that flight. Currently, in many of the airports around the world, the decision to open or close check-in counters is done on an ad hoc basis by human schedulers. In doing so, the schedulers are almost always forced to perform a balancing act in meeting the quality of service stipulated by the …

R&D Project Scheduling When Activities May Fail, Bert De Reyck, Roel Leus

Research Collection Lee Kong Chian School Of Business

An R&D project typically consists of several stages. Due to technological risks, the project may have to be terminated before completion, each stage having a specific likelihood of success. In the project planning and scheduling literature, this technological uncertainty has typically been ignored and project plans are developed only for scenarios in which the project succeeds. In this paper we examine how to schedule projects in order to maximize their expected net present value when the project activities have a probability of failure and when an activity's failure leads to overall project termination. We formulate the problem, show that it …

Efficient Algorithms For Machine Scheduling Problems With Earliness And Tardiness Penalties, Guang Feng, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper, we study the multi-machine scheduling problem with earliness and tardiness penalties and sequence dependent setup times. This problem can be decomposed into two subproblems—sequencing and timetabling. Sequencing focuses on assigning each job to a fixed machine and determine the job sequence on each machine. We call such assignment a semi-schedule. Timetabling focuses on finding an executable schedule from the semi-schedule via idle-time insertion. Sequencing is strongly NP-hard in general. Although timetabling is polynomial-time solvable, it can become a computational bottleneck if the procedure is executed many times within a larger framework. This paper makes two contributions. We …

An Energy-Efficient And Access Latency Optimized Indexing Scheme For Wireless Data Broadcast, Yuxia Yao, Xueyan Tang, Ee Peng Lim, Aixin Sun

Research Collection School Of Computing and Information Systems

Data broadcast is an attractive data dissemination method in mobile environments. To improve energy efficiency, existing air indexing schemes for data broadcast have focused on reducing tuning time only, i.e., the duration that a mobile client stays active in data accesses. On the other hand, existing broadcast scheduling schemes have aimed at reducing access latency through nonflat data broadcast to improve responsiveness only. Not much work has addressed the energy efficiency and responsiveness issues concurrently. This paper proposes an energy-efficient indexing scheme called MHash that optimizes tuning time and access latency in an integrated fashion. MHash reduces tuning time by …

Mabs: Spreadsheet– Based Decision Support For Precision Marketing, Bert De Reyck, Zeger Degraeve

Research Collection Lee Kong Chian School Of Business

In this paper, we describe a decision support system developed for automatically scheduling and optimising broadcasts of advertisements to mobile phones via SMS (Short Message Service) text messaging. The system, MABS or “Mobile Advertising Broadcast Scheduler”, is developed in Microsoft Excel with a link to Lingo, a modelling language and IP solver. It was developed for a London-based company specialized in location-sensitive precision marketing via mobile phones. The system significantly reduced the time required to schedule the broadcasts, and resulted both in increased customer response and revenues.

Webarc: Website Archival Using A Structured Approach, Ee Peng Lim, Maria Marissa

Research Collection School Of Computing and Information Systems

Website archival refers to the task of monitoring and storing snapshots of website(s) for future retrieval and analysis. This task is particularly important for websites that have content changing over time with older information constantly overwritten by newer one. In this paper, we propose WEBARC as a set of software tools to allow users to construct a logical structure for a website to be archived. Classifiers are trained to. determine relevant web pages and their categories, and subsequently used in website downloading. The archival schedule can be specified and executed by a scheduler. A website viewer is also developed to …

Tosa: A Near-Optimal Scheduling Algorithm For Multi-Channel Data Broadcast, Baihua Zheng, Xia Xu, Xing Jin, Dik Lun Lee

Research Collection School Of Computing and Information Systems

Wireless broadcast is very suitable for delivering information to a large user population. In this paper, we concentrate on data allocation methods for multiple broadcast channels. To the best of our knowledge, this is the first allocation model that takes into the consideration of items' access frequencies, items' lengths. and bandwidth of different channels. We first derive the optimal average expected delay for multiple channels for the general case where data access frequencies, data sizes, and channel bandwidths can all be non-uniform. Second, we develop TOSA, a multi-channel allocation method that does not assume a uniform broadcast schedule for data …