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Flexible Services and Manufacturing Journal

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ISSN (Print) 1936-6582 - ISSN (Online) 1936-6590
Published by Springer-Verlag

[2216 journals]

Project portfolio selection under uncertainty with outsourcing opportunities
- Abstract: The paper presents a stochastic optimization model for project portfolio selection under uncertainty about the real efforts required for the execution of the work packages contained in the projects. As a subproblem, the assignment of the work to human resources and the distribution of work over time is addressed. The available workforce is assumed as multi-skilled. Required efforts are modeled as random variables. The recourse action for the case where the available capacities of the internal human resources do not suffice to cover the actual work times consists in delegating parts of the work to external human resources. The staffing-and-scheduling subproblem is solved by means of a Frank-Wolfe type algorithm. To solve the upper-level problem of project portfolio determination, a modification of the Variable Neighborhood Search (VNS) algorithm is applied. Experimental results for a benchmark of synthetically generated test instances and for an illustrative example from the E-Commerce Competence Center Austria are provided.
  PubDate: 2013-06-01
Project scheduling with resource capacities and requests varying with time: a case study
- Abstract: This paper discusses an extension of the classical resource-constrained project scheduling problem in which the resource availability as well as the resource request of the activities may change from period to period. While the applicability of this extension should be obvious, we provide a case study in order to emphasize the need for the extension. A real-world medical research project is presented which has a structure that is typical for many other medical and pharmacological research projects that consist of experiments. Subsequently, we provide a mathematical model and analyze some properties of the extended problem setting. We also introduce a new priority rule heuristic that is based on a randomized activity selection mechanism which makes use of so-called tournaments. Finally, we report our computational results for the original data of the medical research project as well as for a set of systematically generated test instances.
  PubDate: 2013-06-01
An ant-based coordination mechanism for resource-constrained project scheduling with multiple agents and cash flow objectives
- Abstract: We consider a multi-agent extension of the non-preemptive single-mode resource-constrained project scheduling problem with discounted cash flow objectives. Such a problem setting is related to project scheduling problems which involve different autonomous firms where project activities are uniquely assigned to the project parties (agents). Taking into account opportunistic agents and the resulting information asymmetry we propose a general decentralized negotiation approach which uses ideas from ant colony optimization. In the course of the negotiation the agents iteratively vote on proposed project schedules without disclosing preference information regarding cash flow values. Computational experiments serve to analyze the agent-based coordination mechanism in comparison to other approaches from the literature. The proposed mechanism turns out as an effective method for coordinating self-interested agents with conflicting goals which collaborate in resource-constrained projects.
  PubDate: 2013-06-01
Comparison of mixed integer linear programming models for the resource-constrained project scheduling problem with consumption and production of resources
- Abstract: This paper addresses an extension of the resource-constrained project scheduling problem that takes into account storage resources which may be produced or consumed by activities. To solve this problem, we propose the generalization of two existing mixed integer linear programming models for the classical resource-constrained project scheduling problem, as well as one novel formulation based on the concept of event. Computational results are reported to compare these formulations with each other, as well as with a reference method from the literature. Conclusions are drawn on the merits and drawbacks of each model according to the instance characteristics.
  PubDate: 2013-06-01
Resource dedication problem in a multi-project environment
- Abstract: There can be different approaches to the management of resources within the context of multi-project scheduling problems. In general, approaches to multi-project scheduling problems consider the resources as a pool shared by all projects. On the other hand, when projects are distributed geographically or sharing resources between projects is not preferred, then this resource sharing policy may not be feasible. In such cases, the resources must be dedicated to individual projects throughout the project durations. This multi-project problem environment is defined here as the resource dedication problem (RDP). RDP is defined as the optimal dedication of resource capacities to different projects within the overall limits of the resources and with the objective of minimizing a predetermined objective function. The projects involved are multi-mode resource constrained project scheduling problems with finish to start zero time lag and non-preemptive activities and limited renewable and nonrenewable resources. Here, the characterization of RDP, its mathematical formulation and two different solution methodologies are presented. The first solution approach is a genetic algorithm employing a new improvement move called combinatorial auction for RDP, which is based on preferences of projects for resources. Two different methods for calculating the projects’ preferences based on linear and Lagrangian relaxation are proposed. The second solution approach is a Lagrangian relaxation based heuristic employing subgradient optimization. Numerical studies demonstrate that the proposed approaches are powerful methods for solving this problem.
  PubDate: 2013-06-01
On the interaction between roadrunner or railway scheduling and priority lists or resource flow networks
- Abstract: In previous research (Tian and Demeulemeester 2010), we have shown that in realistic situations railway scheduling improves both the stability and the expected project length over roadrunner scheduling. In this paper, we introduce the concept of resource flow networks in this analysis and determine what the impact of combining roadrunner or railway scheduling with priority lists or resource flow networks is on the average project length, the standard deviation of the project length, the timely project completion probability and the stability cost. Extensive computational results will be presented on both small and larger projects and a statistical analysis will be conducted by using SAS PROC GLM, indicating that in smaller projects the optimal combination strongly depends on the performance indicator of interest, while in larger projects a combination of roadrunner scheduling with a resource flow network seems optimal.
  PubDate: 2013-06-01
A new formulation for the project scheduling problem under limited resources
- Abstract: In this paper we propose a new formulation for the Resource Constrained Project Scheduling Problem (RCPSP) and minimum makespan objective. The new formulation exploits three variables, one associated with the start time of an activity, one associated with the finish time of an activity, and the last one associated with the amount of an activity in progress at a given time. We provide an extensive experimentation, and a comparison with known mathematical formulations for the RCPSP in the literature.
  PubDate: 2013-06-01
Project management and scheduling
- PubDate: 2013-06-01
An artificial immune system algorithm for the resource availability cost problem
- Abstract: In this paper, an artificial immune system (AIS) algorithm for the resource availability cost problem (RACP) is presented, in which the total cost of the (unlimited) renewable resources required to complete the project by a pre-specified project deadline should be minimized. The AIS algorithm makes use of mechanisms inspired by the vertebrate immune system and includes different algorithmic components, such as a new fitness function, a probability function for the composition of the capacity lists, and a K-means density function in order to avoid premature convergence. All components are explained in detail and computational results for the RACP are presented.
  PubDate: 2013-06-01
Robust optimization for resource-constrained project scheduling with uncertain activity durations
- Abstract: The purpose of this paper is to propose models for project scheduling when there is considerable uncertainty in the activity durations, to the extent that the decision maker cannot with confidence associate probabilities with the possible outcomes of a decision. Our modeling techniques stem from robust discrete optimization, which is a theoretical framework that enables the decision maker to produce solutions that will have a reasonably good objective value under any likely input data scenario. We develop and implement a scenario-relaxation algorithm and a scenario-relaxation-based heuristic. The first algorithm produces optimal solutions but requires excessive running times even for medium-sized instances; the second algorithm produces high-quality solutions for medium-sized instances and outperforms two benchmark heuristics.
  PubDate: 2013-06-01
An integrated scheduling and control model for multi-mode projects
- Abstract: In today’s highly competitive uncertain project environments, it is of crucial importance to develop analytical models and algorithms to schedule and control project activities so that the deviations from the project objectives are minimized. This paper addresses the integrated scheduling and control in multi-mode project environments. We propose an optimization model that models the dynamic behavior of projects and integrates optimal control into a practically relevant project scheduling problem. From the scheduling perspective, we address the discrete time/cost trade-off problem, whereas an optimal control formulation is used to capture the effect of project control. Moreover, we develop a solution algorithm for two particular instances of the optimal project control. This algorithm combines a tabu search strategy and nonlinear programming. It is applied to a large scale test bed and its efficiency is tested by means of computational experiments. To the best of our knowledge, this research is the first application of optimal control theory to multi-mode project networks. The models and algorithms developed in this research are targeted as a support tool for project managers in both scheduling and deciding on the timing and quantity of control activities.
  PubDate: 2013-06-01
New meta-heuristics for the resource-constrained project scheduling problem
- Abstract: In this paper, we study the resource-constrained project scheduling problem and introduce an annealing-like search heuristic which simulates the cooling process of a gas into a highly-ordered crystal. To achieve this, we develop diversification procedures that simulate the motion of high energy molecules as well as a local refinement procedure that simulates the motion of low energy molecules. We further improve the heuristic by incorporating a genetic algorithm framework. The meta-heuristic algorithms are applied to Kolisch’s PSPLIB J30, J60 and J120 RCPSP instances. Experimental results show that they are effective and are among the best performing algorithms for the RCPSP.
  PubDate: 2013-06-01
An exact reoptimization algorithm for the scheduling of elevator groups
- Abstract: The task of an elevator control is to schedule the elevators of a group such that small waiting and travel times for the passengers are obtained. We present an exact reoptimization algorithm for this problem. A reoptimization algorithm computes a new schedule for the elevator group each time a new passenger arrives. Our algorithm uses column generation techniques and is, to the best of our knowledge, the first exact reoptimization algorithm for a group of passenger elevators. To solve the column generation problem, we propose a Branch & Bound method. The overall algorithm finds high-quality solutions very quickly.
  PubDate: 2013-04-23
Maritime fleet deployment with voyage separation requirements
- Abstract: A dry bulk shipping company is operating its fleet on a number of trade routes and is committed to sail a given number of voyages on these trade routes during the planning period, while trying to derive additional revenue from chartering out ships on short term contracts if possible. The shipping company has agreed with the cargo owners that the voyages of a trade should be fairly evenly spread. This leads to a maritime fleet deployment problem with voyage separation requirements. Two formulations for this problem are presented, one arc flow formulation and one path flow formulation. The voyage separation requirements are modeled either as hard constraints or as soft constraints. Computational results show that the path flow model can be solved for problems of realistic size, and that including voyage separation requirements gives solutions with much better spread of voyages. Solving a real life problem and comparing the solution with a plan made manually by experienced fleet schedulers shows that using the proposed optimization method can both generate increased profit and save the schedulers a lot of work.
  PubDate: 2013-04-02
Master production scheduling and sequencing at mixed-model assembly lines in the automotive industry
- Abstract: The customization of final products in the automotive industry involves a large number of optional parts and leads to a huge variety of operation times at the various stations of the assembly line. The master production scheduling problem (MPS) for high-variant mixed-model assembly lines is to assign the individual customer-defined models of a basic product type to short-term production periods while anticipating the negative impacts of an unbalanced model sequence at the lower planning level. We propose a mathematical model formulation for the MPS and develop heuristic solution procedures that attempt to minimize the workload variability. Specifically, these procedures anticipate decisions on the mixed-model sequence and the resulting work overload at stations which has to be balanced by the assignment of utility workers. Furthermore, an integrated planning approach for solving the MPS and the production sequencing problem is proposed.
  PubDate: 2013-02-27
Scheduling movements in the network of an express service provider
- Abstract: Express service providers manage shipments from senders to receivers under strict service level agreements. Such shipments are usually not sufficient to justify a single transportation, so it is preferred to maximize consolidation of these shipments to reduce cost. The consolidation is organized via depots and hubs: depots are local sorting centers that take care of the collection and delivery of the parcels at the customers, and hubs are used to consolidate the transportation between the depots. A single transportation between two locations, carried out by a certain vehicle at a specific time, is defined as a movement. In this paper, we address the problem of scheduling all movements in an express network at minimum cost. Our approach allows to impose restrictions on the number of arriving/departing movements at the hubs so that sufficient handling capacity is ensured. As the movement scheduling problem is complex, it is divided into two parts: one part concerns the movements between depots and hubs; the other part considers the movements between the hubs. We use a column generation approach and a local search algorithm to solve these two subproblems, respectively. Computational experiments show that by using this approach the total transportation costs are decreased.
  PubDate: 2013-02-01
The impact of carbon footprinting aggregation on realizing emission reduction targets
- Abstract: A variety of activity-based methods exist for estimating the carbon footprint in transportation. For instance, the greenhouse gas protocol suggests a more aggregate estimation method than the Network for Transport and Environment (NTM) method. In this study, we implement a detailed estimation method based on NTM and different aggregate approaches for transportation carbon emissions in the dynamic lot sizing model. Analytical results show the limitations of aggregate models for both accurate estimation of real emissions and risks of compliance with carbon constraints (e.g., carbon caps). Extensive numerical experimentation shows that the magnitude of errors can be substantial. We provide insights under which limited conditions aggregate estimations can be used safely and when more detailed estimates are appropriate.
  PubDate: 2013-01-01
Susceptibility of optimal train schedules to stochastic disturbances of process times
- Abstract: This work focuses on the stochastic evaluation of train schedules computed by a microscopic scheduler of railway operations based on deterministic information. The research question is to assess the degree of sensitivity of various rescheduling algorithms to variations in process times (running and dwell times). In fact, the objective of railway traffic management is to reduce delay propagation and to increase disturbance robustness of train schedules at a network scale. We present a quantitative study of traffic disturbances and their effects on the schedules computed by simple and advanced rescheduling algorithms. Computational results are based on a complex and densely occupied Dutch railway area; train delays are computed based on accepted statistical distributions, and dwell and running times of trains are subject to additional stochastic variations. From the results obtained on a real case study, an advanced branch and bound algorithm, on average, outperforms a First In First Out scheduling rule both in deterministic and stochastic traffic scenarios. However, the characteristic of the stochastic processes and the way a stochastic instance is handled turn out to have a serious impact on the scheduler performance.
  PubDate: 2013-01-01
Health care management
- PubDate: 2012-12-01
Reduce fluctuations in capacity to improve the accessibility of radiotherapy treatment cost-effectively
- Abstract: This paper is motivated by a case study to reduce the throughput times for radiotherapy treatment. The goal is to find a cost-effective way to meet future throughput targets. A combination of queuing theory and computer simulation was used. First, computer simulation to detect the bottleneck(s) in a multi-step radiotherapy process. Despite, the investment in an additional linear accelerator, the main bottleneck turned out to be the outpatient department (OPD). Next, based on queuing theory, waiting times were improved by reducing the fluctuations in the OPD capacity. Computer simulation was used again to quantify the effect on the total throughput time of a radiotherapy patient. The results showed a reduction in both access times as well as waiting times prior to the consecutive steps: the preparation phase and actual treatment. The paper concludes with practical suggestions on how to reduce the fluctuations in capacity, and seems of interest for other radiotherapy departments or other multi-step situations in a hospital.
  PubDate: 2012-12-01