807 research outputs found

    Minimizing total completion time subject to job release dates and preemption penalties

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    2004-2005 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

    Order Acceptance and Scheduling: A Taxonomy and Review

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    Over the past 20 years, the topic of order acceptance has attracted considerable attention from those who study scheduling and those who practice it. In a firm that strives to align its functions so that profit is maximized, the coordination of capacity with demand may require that business sometimes be turned away. In particular, there is a trade-off between the revenue brought in by a particular order, and all of its associated costs of processing. The present study focuses on the body of research that approaches this trade-off by considering two decisions: which orders to accept for processing, and how to schedule them. This paper presents a taxonomy and a review of this literature, catalogs its contributions and suggests opportunities for future research in this area

    Single-machine scheduling with stepwise tardiness costs and release times

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    We study a scheduling problem that belongs to the yard operations component of the railroad planning problems, namely the hump sequencing problem. The scheduling problem is characterized as a single-machine problem with stepwise tardiness cost objectives. This is a new scheduling criterion which is also relevant in the context of traditional machine scheduling problems. We produce complexity results that characterize some cases of the problem as pseudo-polynomially solvable. For the difficult-to-solve cases of the problem, we develop mathematical programming formulations, and propose heuristic algorithms. We test the formulations and heuristic algorithms on randomly generated single-machine scheduling problems and real-life datasets for the hump sequencing problem. Our experiments show promising results for both sets of problems

    Single machine scheduling with release dates and job delivery to minimize the makespan

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    AbstractIn single machine scheduling with release dates and job delivery, jobs are processed on a single machine and then delivered by a capacitated vehicle to a single customer. Only one vehicle is employed to deliver these jobs. The vehicle can deliver at most c jobs at a shipment. The delivery completion time of a job is defined as the time at which the delivery batch containing the job is delivered to the customer and the vehicle returns to the machine. The objective is to minimize the makespan, i.e., the maximum delivery completion time of the jobs. When preemption is allowed to all jobs, we give a polynomial-time algorithm for this problem. When preemption is not allowed, we show that this problem is strongly NP-hard for each fixed c≥1. We also provide a 53-approximation algorithm for this problem, and the bound is tight

    Shop Scheduling In The Presence Of Batching, Sequence-dependent Setups And Incompatible Job Families Minimizing Earliness And Tardiness Penalties

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    The motivation of this research investigation stems from a particular job shop production environment at a large international communications and information technology company in which electro-mechanical assemblies (EMAs) are produced. The production environment of the EMAs includes the continuous arrivals of the EMAs (generally called jobs), with distinct due dates, degrees of importance and routing sequences through the production workstations, to the job shop. Jobs are processed in batches at the workstations, and there are incompatible families of jobs, where jobs from different product families cannot be processed together in the same batch. In addition, there are sequence-dependent setups between batches at the workstations. Most importantly, it is imperative that all product deliveries arrive on time to their customers (internal and external) within their respective delivery time windows. Delivery is allowed outside a time window, but at the expense of a penalty. Completing a job and delivering the job before the start of its respective time window results in a penalty, i.e., inventory holding cost. Delivering a job after its respective time window also results in a penalty, i.e., delay cost or emergency shipping cost. This presents a unique scheduling problem where an earlinesstardiness composite objective is considered. This research approaches this scheduling problem by decomposing this complex job shop scheduling environment into bottleneck and non-bottleneck resources, with the primary focus on effectively scheduling the bottleneck resource. Specifically, the problem of scheduling jobs with unique due dates on a single workstation under the conditions of batching, sequence-dependent iii setups, incompatible job families in order to minimize weighted earliness and tardiness is formulated as an integer linear program. This scheduling problem, even in its simplest form, is NP-Hard, where no polynomial-time algorithm exists to solve this problem to optimality, especially as the number of jobs increases. As a result, the computational time to arrive at optimal solutions is not of practical use in industrial settings, where production scheduling decisions need to be made quickly. Therefore, this research explores and proposes new heuristic algorithms to solve this unique scheduling problem. The heuristics use order review and release strategies in combination with priority dispatching rules, which is a popular and more commonly-used class of scheduling algorithms in real-world industrial settings. A computational study is conducted to assess the quality of the solutions generated by the proposed heuristics. The computational results show that, in general, the proposed heuristics produce solutions that are competitive to the optimal solutions, yet in a fraction of the time. The results also show that the proposed heuristics are superior in quality to a set of benchmark algorithms within this same class of heuristic

    The preemptive resource-constrained project scheduling problem subject to due dates and preemption penalties: An integer programming approach

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    Extensive research has been devoted to resource constrained project scheduling problem. However, little attention has been paid to problems where a certain time penalty must be incurred if activity preemption is allowed. In this paper, we consider the project scheduling problem of minimizing the total cost subject to resource constraints, earliness-tardiness penalties and preemption penalties, where each time an activity is started after being preempted; a constant setup penalty is incurred. We propose a solution method based on a pure integer formulation for the problem. Finally, some test problems are solved with LINGO version 8 and computational results are reported

    A hierarchical approach to multi-project planning under uncertainty

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    We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. A positioning framework is proposed to distinguish between different types of project-driven organisations, which is meant to aid project management in the choice between the various existing planning approaches. We discuss the current state of the art of hierarchical planning approaches both for traditional manufacturing and for project environments. We introduce a generic hierarchical project planning and control framework that serves to position planning methods for multi-project planning under uncertainty. We discuss multiple techniques for dealing with the uncertainty inherent to the different hierarchical stages in a multi-project organisation. In the last part of this paper we discuss two cases from practice and we relate these practical cases to the positioning framework that is put forward in the paper

    Scheduling under uncertainty for a Single-Hub Intermodal Freight System

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    This thesis addresses the optimization of an intermodal system with freight transfers at a single hub. It investigates the transportation processes and constraints that arise in a system's recovery after a major disruption during which backlogs have accumulated along the routes. When dealing with the backlogs, the system operator must coordinate the transportation processes and control the inflow of freight to the terminal in order to avoid overloading its storage facilities, which might reduce the throughput of the system. The coordination of transportation processes during the system's recovery can further improve the overall system performance by reducing the dwell time, increasing vehicle utilization and reducing late delivery penalties. This work focuses on the scheduling problem and develops an approach that would help the system operator reduce the overall system cost while taking into account the constraints arising in actual intermodal and intra-modal systems. Assuming that the schedule on some routes is exogenously determined and inflexible, we seek to optimize the schedules of vehicles on remaining routes. Models are developed that minimize the total cost of operating an intermodal system with freight transfers at one hub by optimizing the departure times of vehicles on the routes with flexible schedules. This model can be solved numerically without the approximations of alternative methods such as simulation. Moreover, it can be successfully applied to situations when statistical or queuing analyses are not applicable due to the small number of events (vehicle arrivals). We specifically analyze an intermodal system consisting of multiple feeder truck routes and multiple main airline routes. The specific example of two transportation modes was used to make the development and application of the model easier to understand. However, the mathematical model developed in this thesis is applicable to any other combination of transportation modes using discrete vehicles
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