Scheduling

Simulation Optimization for the Stochastic Economic Lot Scheduling Problem with Sequence-Dependent Setup Times

  • Nils Löhndorf
  • Stefan Minner
  • Manuel Riel
    • Categories Optimization of Simulated Systems, Scheduling, Stochastic Approaches Tags , , , , ,

    We consider the stochastic economic lot scheduling problem (SELSP) with lost sales and random demand, where switching between products is subject to sequence-dependent setup times. We propose a solution based on simulation optimization using an iterative two-step procedure which combines global policy search with local search heuristics for the traveling salesman sequencing subproblem. To optimize … Read more

    Improving the Performance of Stochastic Dual Dynamic Programming

  • Vitor de Matos
  • Erlon Finardi
  • Andrew B. Philpott
    • Categories Scheduling, Stochastic Programming

    This paper is concerned with tuning the Stochastic Dual Dynamic Programming algorithm to make it more computationally efficient. We report the results of some computational experiments on a large-scale hydrothermal scheduling model developed for Brazil. We find that the best improvements in computation time are obtained from an implementation that increases the number of scenarios … Read more

    Stochastic integer programming based algorithms for adaptable open block surgery scheduling

  • Camilo Mancilla
  • Robert H. Storer
    • Categories Applications - OR and Management Sciences, Scheduling, Stochastic Programming Tags , ,

    We develop algorithms for adaptable schedule problems with patient waiting time, surgeon waiting time, OR idle time and overtime costs. Open block surgery scheduling of multiple surgeons operating in multiple operating rooms (ORs) motivates the work. We investigate creating an “adaptable” schedule of surgeries under knowledge that this schedule will change (be rescheduled) during execution … Read more

    Hybridizing VNS and path-relinking on a particle swarm framework to minimize total flowtime

  • Wagner Emanoel Costa
  • Elizabeth G. Goldbarg
  • Marco César Goldbarg
    • Categories Meta Heuristics, Scheduling Tags , , , ,

    This paper presents a new hybridization of VNS and path-relinking on a particle swarm framework for the permutational fowshop scheduling problem with total flowtime criterion. The operators of the proposed particle swarm are based on path-relinking and variable neighborhood search methods. The performance of the new approach was tested on the bechmark suit of Taillard, … Read more

    Flow shop scheduling with peak power consumption constraints

  • K. Fang
  • Nelson A. Uhan
  • John W. Sutherland
  • Fu Zhao
    • Categories Combinatorial Optimization, Integer Programming, Scheduling Tags , , , , ,

    We study scheduling as a means to address the increasing energy concerns in manufacturing enterprises. In particular, we consider a flow shop scheduling problem with a restriction on peak power consumption, in addition to the traditional time-based objectives. We investigate both mathematical programming and combinatorial approaches to this scheduling problem, and test our approaches with … Read more

    An Exact Algorithm for Two-stage Robust Optimization with Mixed Integer Recourse Problems

  • Bo Zeng
  • Long Zhao
    • Categories Applications - OR and Management Sciences, Robust Optimization, Scheduling Tags , , ,

    In this paper, we consider a linear two-stage robust optimization model with a mixed integer recourse problem. Currently, this type of two-stage robust optimization model does not have any exact solution algorithm available. We first present a set of sufficient conditions under which the existence of an optimal solution is guaranteed. Then, we present a … Read more

    Risk neutral and risk averse Stochastic Dual Dynamic Programming method

  • Joari Paulo da Costa
  • Alexander Shapiro
  • Murilo Pereira Soares
  • Wajdi Tekaya
    • Categories Dynamic Programming, Scheduling, Stochastic Programming Tags , , , , , ,

    In this paper we discuss risk neutral and risk averse approaches to multistage (linear) stochastic programming problems based on the Stochastic Dual Dynamic Programming (SDDP) method. We give a general description of the algorithm and present computational studies related to planning of the Brazilian interconnected power system. Citation ArticleDownload View PDF

    Daily Scheduling of Nurses in Operating Suites

  • Jonathan Bard
  • Gino J. Lim
  • Victoria Jordan
  • Arezou Mobasher
    • Categories Applications - Science and Engineering, Scheduling Tags , ,

    This paper provides a new multi-objective integer programming model for the daily scheduling of nurses in operating suites. The model is designed to assign nurses to di erent surgery cases based on their specialties and competency levels, subject to a series of hard and soft constraints related to nurse satisfaction, idle time, overtime, and job changes … Read more

    A General Framework for Designing Approximation Schemes for Combinatorial Optimization Problems with Many Objectives Combined Into One

  • Shashi Mittal
  • Andreas S. Schulz
    • Categories Approximation Algorithms, Robust Optimization, Scheduling Tags , , ,

    In this paper, we present a general framework for designing approximation schemes for combinatorial optimization problems in which the objective function is a combination of more than one function. Examples of such problems include those in which the objective function is a product or ratio of two linear functions, parallel machine scheduling problems with the … Read more

    Optimal Job Scheduling with Day-ahead Price and Random Local Distributed Generation: A Two-stage Robust Approach

  • Mehrnaz Abdollahian
  • Bo Zeng
  • Anna Danandeh
  • Long Zhao
    • Categories Robust Optimization, Scheduling Tags , , , ,

    In this paper, we consider a job scheduling problem with random local generation, in which some jobs must be scheduled day-ahead while the others can be scheduled in a real time fashion. To capture the randomness of the local distributed generation, we develop a two-stage robust optimization model by assuming an uncertainty set without probability … Read more