Guohua Wan

Shanghai Jiao Tong University | SJTU · Department of Management Science

Atrial fibrillation (AF), the most prevalent cardiac rhythm disorder, significantly increases hospitalization and health risks. Reverting from AF to sinus rhythm (SR) often requires intensive interventions. This study presents a deep-learning model capable of predicting the transition from SR to AF on average 30.8 min before the onset appears, with...

Problem definition: Multistage service is common in healthcare. One widely adopted approach to manage patient visits in multistage service is to provide patients with visit itineraries that specify personalized appointment time for each patient at each service stage. We study how to design such visit itineraries. Methodology/results: We develop the...

Erratum to “Competitive Two-Agent Scheduling and Its Applications” The paper “Competitive Two-Agent Scheduling and Its Applications” by Leung, Pinedo, and Wan appeared in Operations Research in 2010. Because competitive agent scheduling has become an active area of research, the paper has garnered its share of citations over the years. This particu...

Treatment Planning for Mass Casualty Incidents The existing emergency response guidelines emphasize prioritizing the treatment of victims with initially critical health conditions, but tend to overlook the potential deterioration of less critical victims. Such deterioration can result in prolonged treatment times and irreversible health damages. In...

Problem definition: Intraproject learning in project scheduling involves the use of learning among the similar tasks in a project to improve the overall performance of the project schedule. Under intraproject learning, knowledge gained from completing some tasks in a project is used to execute similar later tasks in the same project more efficientl...

Problem definition: Multi-stage service is common in healthcare. One widely adopted approach to manage patient visits in multi-stage service is to provide patients with visit itineraries, which specify individualized appointment time for each patient at each service stage. We study how to design such visit itineraries. Methodology/results: We devel...

We study a two-stage hybrid flow shop problem arising from a fine chemicals production facility, where the first stage is a continuous chemical reaction process and the second stage is a discrete filling-packaging process. The objective is to minimise the total weighted completion time through batching of the jobs and scheduling of the batches at f...

A bstract Atrial Fibrillation (AF) is the most common cardiac rhythm disorder. It is associated with increased hospitalization, risk of heart failure, and risk of stroke. Once on AF, it can sometimes be difficult to revert to sinus rhythm (SR), potentially requiring pharmacological or electrical cardioversion. Earlier warning of an imminent switch...

Hierarchical time series arise in various fields such as manufacturing and services when the products or services can be hierarchically structured. “Top-Down” and “Bottom-Up” forecasting approaches are often used for forecasting such hierarchical time series. In this paper, we develop a new hybrid approach (HA) with step-size aggregation for hierar...

Motivated by a real problem in a big hospital in China, we study a daily surgery scheduling problem with operating room eligibility and dedicated surgeon. We model the problem as a parallel machine scheduling problem with machine and resource constraints to minimise the makespan, and innovatively propose an adaptive composite dispatching method to...

Motivated by a real-world problem in an automobile manufacturing firm, we study the multi-level multi-stage lot-sizing and scheduling problem with demand information updating. The objective is to determine the quantities and sequences of production on different production stages to minimize the total costs of production and inventory. We employ the...

We consider a multi-period lot-sizing problem with multiple products and multiple suppliers. Demand is deterministic and time-varying. The objective is to determine order quantities to minimize the total cost over a finite planning horizon. This problem is strongly NP-hard. For a special case, we extend the classical zero-inventory-ordering princip...

We consider the classical appointment scheduling problem that does not have a session length constraint. The decision is to determine job allowances to minimize total expected weighted costs of waiting times of jobs and idle times of the service provider. In particular, we study a simple yet effective scheduling policy – the so‐called “constant” po...

Background Market-applicable concurrent electrocardiogram (ECG) diagnosis for multiple heart abnormalities that covers a wide range of arrhythmias, with better-than-human accuracy, has not yet been developed. We therefore aimed to engineer a deep learning approach for the automated multilabel diagnosis of heart rhythm or conduction abnormalities by...

Motivated by the practices of home services, we consider an integrated routing and appointment scheduling problem with stochastic service times. Given a set of customers with known locations and random service times, the professional operator has to visit each customer location exactly once to provide the services. The problem is to determine the v...

We consider financing and coordinating issues in a supply chain with one supplier (she) and one manufacturer (he), where the supplier is capital-constrained and her production yield is random. Facing shortage of capital, the supplier may use two financing sources to facilitate her production: bank loan from a commercial bank, or advance payment fro...

Hierarchical forecasting data

We consider the appointment scheduling problem, which determines the job allowance over the planning horizon. In particular, we study a simple yet effective scheduling policy-the so-called "constant" policy, which allocates a constant job allowance for each appointment. Prior studies on appointment scheduling suggest a "dome" shape structure for th...

Hierarchical time series arise in manufacturing and service industries when the products or services have the hierarchical structure, and top-down and bottom-up methods are commonly used to forecast the hierarchical time series. One of the critical factors that affect the performance of the two methods is the correlation between the data series. Th...

Make-to-order (MTO) is a popular production strategy commonly used by manufacturers selling customized products. Dynamic pricing is a popular tactical tool commonly used by sellers to match supply with demand when there is a limited capacity and high demand uncertainty over time. In this paper, we consider joint pricing and production scheduling de...

Multi-Level Multi-Stage Lot-sizing and Scheduling with Demand Information Updating

In outpatient services, it is critical to schedule patients for physicians to reduce both patients waiting and physicians overtime working. In this paper, we regard the problem as an online scheduling problem and based on analysis of a real data set from a big hospital in China, we develop a dynamic programming model to solve the problem. We propos...

Despite the prevalence and significance of walk-ins in healthcare, we know relatively little about how to plan and manage the daily operations of a healthcare facility that accepts both scheduled and walk-in patients. In this paper, we take a data-analytics approach and develop an optimization model to determine the optimal appointment schedule in...

In home services (such as home care), a service provider (with a set of service teams) provides services to a set of geographically distributed customers. A critical operations decision in such services is to assign and route the service teams, while making appointment times for the customers so as to efficiently deliver the services. For this purp...

Despite the prevalence and significance of walk-ins in healthcare, we know relatively little about how to plan and manage the daily operations of a healthcare facility that accepts both scheduled and walk-in patients. In this paper, we develop the first optimization model to determine the optimal appointment schedule in the presence of potential wa...

We study a parallel machine scheduling problem, where a job j can only be processed on a specific subset of machines Mj, and the Mj subsets of the n jobs are nested. We develop a two-phase heuristic for minimizing the total weighted tardiness subject to the machine eligibility constraints. In the first phase, we compute the factors and statistics t...

In this paper, we consider an online order scheduling problem with the same order size on two identical machines. The objective is to minimize the makespan. An order list [Formula: see text] is given, where [Formula: see text] is a positive integer. For the problem under study, we assume that [Formula: see text] ([Formula: see text]), that is to sa...

Due date quotation and scheduling are important tools to match demand with production capacity in the MTO (make-to-order) environment. We consider an order scheduling problem faced by a manufacturing firm operating in an MTO environment, where the firm needs to quote a common due date for the customers, and simultaneously control the processing tim...

We consider single machine scheduling problems with deteriorating jobs and SLK/DIF due window assignment, where the deteriorating rates of jobs are assumed to be job-dependent. We consider two different objectives under SLK and DIF due window assignment, respectively. The first objective is to minimise total costs of earliness, tardiness, due windo...

We study a problem arising from surgical operations scheduling and model it as a resource-constrained machine scheduling problem with machine eligibility restriction to minimize the makespan. By decomposing the problem into two sub-problems, we develop effective heuristic algorithms to solve the problem. We test the proposed algorithms on randomly...

For a classical order quantity/pricing problem, we present a geometric programming (GP) approach to find the optimal selling price, order quantity and quality level to maximize the profit for the retail firm. Traditional models such as EOQ are not able to handle the nonlinearity of costs and demand. We adopt the GP approach and make a proper transf...

We consider the problem of determining the optimal schedules for a given sequence of jobs on a single processor. The objective is to minimize the expected total cost incurred by job waiting and processor idling, where the job processing times are random variables. It is known in the prior literature that if the processing times are integers and the...

This paper is concerned with a semi-online scheduling problem with combined information on two identical parallel machines to minimize the makespan, where all the jobs have processing times in the interval \([1,\,t]\) \((t\ge 1)\) and the jobs arrive in non-increasing order of their processing times. The objective is to minimize the makespan. For \...

In this paper we consider several semi-online scheduling problems on two identical machines with combined information. The objective of each problem is to minimize the makespan. The first problem is semi-online scheduling with known optimal solution value and maximum job size. We obtain a lower bound 65 and design an optimal algorithm with a compet...

This paper examines the impact of financing on the performance of a two-level supply chain consisting of a supplier and a budget-constrained retailer. To carry out our study, we set up a three-stage Stackelberg game under a wholesale price contract with a financial market. We show that financing from a competitive financial market can create value...

We consider an integrated order selection and production scheduling problem where a make-to-order (MTO) manufacturer has to select a subset of the orders to process so as to maximise the total profit, and sequence-dependent setup times and costs are incurred between the manufacturing of different classes of products. The problem is formulated as th...

Many applications, such as telecommunication and commercial video broadcasting systems, computer and networks, and Web mining, require modeling data streams that exhibit context dependency. Context dependency refers to the fact that the statistical distribution of a new sample is heavily conditioned by a set of the most recent samples that precedes...

This paper is concerned with a modified Technology Acceptance Model (TAM) that includes subjective norm and technology trust as antecedents of adoption intention. Although much of previous research has included subjective norm as an adoption factor, the results obtained are not consistent. This study suggests that subjective norm is salient when ad...

We consider several two-agent scheduling problems with controllable job processing times, where agents A and B have to share either a single machine or two identical machines in parallel while processing their jobs. The processing times of the jobs of agent A are compressible at additional cost. The objective function for agent B is always the same...

We consider a scheduling environment with m (m ≥ 1) identical machines in parallel and two agents. Agent A is responsible for n₁ jobs and has a given objective function with regard to these jobs; agent B is responsible for n₂ jobs and has an objective function that may be either the same or different from the one of agent A. The problem is to find...

In this article, we study a class of new scheduling models where time slot costs have to be taken into consideration. In such models, processing a job will incur certain cost which is determined by the time slots occupied by the job in a schedule. The models apply when operational costs vary over time. The objective of the scheduling models is to m...

Motivated by just-in-time manufacturing, we consider a single machine scheduling problem with dual criteria, i.e., the minimization of the total weighted earliness subject to minimum number of tardy jobs. We discuss several dominance properties of optimal solutions. We then develop a heuristic algorithm with time complexity O(n3) and a branch and b...

A single machine scheduling problem with fixed jobs is considered, where the fixed jobs have to be scheduled in pre-specified time windows while the other jobs, called free jobs, have distinct release dates and are allowed to be preempted. The objective of the problem is to minimize the total number of tardy jobs. This problem can be denoted as 1|F...

We consider the problem of preemptively scheduling n imprecise computation tasks on m⩾1 uniform processors, with each task Ti having two weights wi and . Three objectives are considered: (1) minimizing the maximum w′-weighted error; (2) minimizing the total w-weighted error subject to the constraint that the maximum w′-weighted error is minimized;...

This paper discusses the problem of simultaneously selecting and scheduling parallel machines to minimize the sum of machine holding cost and job tardiness cost. A combinatorial optimization model is developed for this purpose. Solving the developed model is NP-hard. A heuristic algorithm is developed to locate the optimal or near optimal solutions...

We consider a problem of maximizing the service of a carousel storage system from which items are removed in groups, where each group consists of a certain given number of items of each type. Kim (Comput. Oper. Res., forthcoming) has developed an algorithm for solving this problem with a running time of O(j2). In this article, we present an algorit...

The chapter focuses on a summary of the contemporary development of workflow management systems in collaborative commerce. The technical facet is demonstrated from perspectives of architectures, standards, and system analysis. The business requirements and application scenarios are exemplified in knowledge sharing, marketing services, and procureme...

This paper is concerned with a joint production and delivery scheduling problem in two level supply chains, i.e., the schedule of both production and delivery (transportation) are simultaneously minimizes the total cost in the supply chain. This joint scheduling problem is difficult to tackle using analytical approaches. A distributed agent based a...

The chapter focuses on a summary of the contemporary development of workflow management systems in collaborative commerce. The technical facet is demonstrated from perspectives of architectures, standards, and system analysis. The business requirements and application scenarios are exemplified in knowledge sharing, marketing services, and procureme...

In the last two decades, various approximation approaches, such as dispatching rules, shifting bottleneck heuristic and local search methods, are proposed for solving the job shop scheduling problem. As one of the local search methods, taboo search provides a promising alternative for the job shop scheduling problem; however, it has to be tailored...

This paper presents a literature survey of single machine bicriteria scheduling problems. First a framework is proposed for classification of single machine bicriteria scheduling problems from four aspects, namely, nature of problems, machine environments, performance measures, and scheduling criteria. The survey summarizes related references with...

A single machine scheduling problem with distinct due windows to minimize total weighted earliness and tardiness is examined. A mathematical formulation of the problem is first presented and several important properties are studied to facilitate the solution process. An optimal timing algorithm is then proposed to determine completion times for eac...

This article analyzes the computational complexity of a single machine scheduling problem to minimize total compression plus weighted flow cost. Vickson [Oper. Res. 28 (1980) 1155–1167] studied this problem and conjectured that it was NP-hard. The complexity of this problem remained open since then. We give a positive answer to this conjecture, sho...

In the last decade, various approximation approaches, such as dispatching rules, shifting bottleneck heuristic and local search methods, are proposed for the job shop scheduling problem. As one of the local search methods, taboo search provides a promising alternative for the job shop scheduling problem; however, it has to be tailored each time wit...

We study a dynamic job shop scheduling problem to minimize total weighted tardiness. Since it is a strongly NP-hard problem, the typical and efficient solution approach is to use dispatching rules; however, the performance of these simple dispatching rules is usually far from satisfactory. A fuzzy logic system is proposed and designed to dynamicall...

The importance of research for rapid and automated model construction of decision support systems is prominent and recognized. In the literature, research on model construction methods has been conducted using either component-based approaches or artificial intelligent approaches; however, these methods are usually incapable of handling dynamic con...

We consider a nonpreemptive single machine common due window scheduling problem where the job processing times are controllable with linear costs and the due window is movable. The objective is to find a job sequence, a processing time for each job, and a position of the common due window to minimize the total cost of weighted earliness/tardiness a...

In this paper, we studied a crane scheduling problem, i.e., the scheduling of RMCs to minimize the total weighted remaining work for the blocks in a terminal storage yard. The approach is a mix of planning method from AI and optimization methods based on MIP formulation. We implemented a DSS to incorporate both AI techniques and OR models. The expe...

This note is concerned with the problem of scheduling a set of jobs with predetermined order on a single processor. The objective is to minimize the expected total cost incurred by job waiting and processor idling, where the job processing times are discrete random variables. We extend the scope of the discussion in Begen and Queyranne [2011] to pi...

We consider several competitive agent scheduling problems with controllable processing times, where two agents A and B compete for a single machine to process their jobs. The objective function for agent B is always the same, namely f max . Several different objective functions are considered for agent A, including the total compression cost subjec...

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2000. Includes bibliographical references (leaves 129-147).