Xiangtong Qi

A logistics scheduling model: scheduling and transshipment for two processing centers

Logistics scheduling refers to problems in which decisions on job scheduling and transportation are integrated into a single framework. A logistics scheduling model for two processing centers that are located in different cities is presented. Each processing center has its own customers. When the demand in one processing center exceeds its processing capacity, it is possible to use part of the capacity of the other processing center subject to a job transshipment delay. Such a coordinated scheduling situation can be modeled as a parallel-machine scheduling problem with transshipment between the machines. We study problems with different objective functions and constraints, and propose various algorithms to solve these problems. Discussions on the benefits and incentives for the coordinated approach are presented.

Disruption management : Framework, Models and Applications

This pioneering book addresses the latest research findings and application results on disruption management, which is the study of how to dynamically recover a predetermined operational plan when various disruptions prevent the original plan from being executed smoothly. A disruption management system will help decision-makers respond to disruptive events in real time so that the cost incurred by the disruption is reduced to a minimum. The impact of such systems is significant. For example, each year the disruption management system for US airlines generates savings of tens of millions of dollars.

A Production-Inventory System with Markovian Capacity and Outsourcing Option

We study the optimal production-inventory-outsourcing policy for a firm with Markovian in-house production capacity that faces independent stochastic demand and has the option to outsource. We find very simple optimal policy forms under fairly reasonable assumptions. In addition, when the capacity Markov process is stochastically monotone, the policy parameters decrease in the firms current capacity level under additional assumptions. All these results extend to the infinite-horizon and undiscounted-cost cases. We analyze comparative statics and the necessity of some technical conditions, and discuss when the outsourcing option is more valuable.

Coordinating dyadic supply chains when production costs are disrupted

This paper studies a supply chain coordination problem under production cost disruptions. When a production cost disruption occurs, the coordination scheme designed for the initially estimated production cost needs to be revised. To resolve this issue, it is necessary to explicitly consider the possible deviation costs caused by any changes in the original production plan. How to model the production cost disruptions and their impacts, and how to design coordination schemes under disruptions is discussed. Results obtained under various scenarios including the cases of a single retailer and multiple retailers, the cases of linear and nonlinear demand-price functions, and different wholesale policies are presented.

Coordinated Logistics Scheduling for In-House Production and Outsourcing

In this paper, we address a new scheduling model for a firm with an option of outsourcing. A job can be processed by either in-house production or outsourcing. All outsourced jobs have to be transported back to the firm in batches, and the transportation costs have to be taken into account. We model the situation as a scheduling problem with transportation considerations. We discuss four commonly used objective functions, and solve them by dynamic programming algorithms. Note to Practitioners-An efficient supply chain management needs the coordination of production and transportation. Such problems exist in many different scenarios. This research considers a particular problem for a firm that has an option of using a subcontractor to fulfill part of its orders. The production schedule has to be coordinated with logistics issues for the transportation from the subcontractor to the firm. The purposes of this paper are twofold. First, we build models and provide optimal solutions for the specific cases discussed in this paper. Second, we hope to raise the issue of coordinated logistics scheduling, and motivate future research on more complicated models.

A note on worst-case performance of heuristics for maintenance scheduling problems

We study a machine scheduling model in which job scheduling and machine maintenance activities have to be considered simultaneously. We develop the worst-case bounds for some heuristic algorithms, including a sharper worst-case bound of the SPT schedule than the results in the literature, and another bound of the EDD schedule.

Order splitting with multiple capacitated suppliers

This paper studies an integrated decision making model for a supply chain system where a manufacturer faces a price-sensitive demand and multiple capacitated suppliers, two issues that are often considered separately in the literature. The goal is to maximize total profit by determining an optimal selling price and at the same time acquiring enough supplying capacity. The problem is proved to be NP-hard in the ordinary sense, a heuristic algorithm and an optimal dynamic programming algorithm are developed. Computational experiments are conducted to study the efficiency and effectiveness of the algorithms. Some managerial insights are observed.

Storage space allocation models for inbound containers in an automatic container terminal

This paper studies the problem of improving the operations efficiency for retrieving inbound containers in a modern automatic container terminal. In the terminal, when an external truck arrives to collect a container stored in a specific container block, it waits at one end of the block where an automatic stack crane will retrieve the container and deliver it to the truck. With the aim of reducing the expected external truck waiting time which is determined by how the containers are stored in a block, we propose two correlated approaches for the operations efficiency improvement, (1) by designing an optimized block space allocation to store the inbound containers after they are discharged from vessels, and (2) by conducting overnight re-marshaling processes to re-organize the block space allocation after some containers are retrieved. For the block space allocation problem, we consider three optimization models under different strategies of storing containers, namely, a non-segregation model, a single-period segregation model, and a multiple-period segregation model. Optimal solution methods are proposed for all three models. For the re-marshaling problem with a given time limit, we find that the problem is NP-hard and develop a heuristic algorithm to solve the problem. We then use simulation to validate our models and solution approaches. Simulation results reveal important managerial insights such as the advantage of the multiple-period segregation over the myopic single-period segregation, the possibility of overflow of the segregation model, and the benefit of re-marshaling.

An acquisition policy for a multi-supplier system with a finite-time horizon

We study the problem of a manufacturer who outsources a single product to multiple capacitated suppliers. Given a pool of potential suppliers, a decision has to be made about which supplier(s) to use, and how much and how often to purchase from each selected supplier. We build an EOQ-type model with a finite-time horizon, which differs from the existing model in the literature with an infinite-time horizon. We design a dynamic programming and a scatter search algorithm to solve the problem, and provide computational results to show the effectiveness of the proposed methods.

Single machine scheduling with assignable due dates

This paper introduces a new subclass of machine scheduling problems in which due dates are treated as variables and must be assigned to the individual jobs. A solution then is a sequence of jobs along with due date assignments. In contrast to existing due date assignment models, solutions to the proposed problems do not depend on predetermined rules or the requirement that due dates be assigned in the same order as the sequence. The single machine case is investigated in detail Complexity results are presented for all common objective functions and processing restrictions. The analysis shows that in a number of instances polynomial time algorithms are available though most problems that are intractable under traditional due date definitions remain so.