Modelling and planning public cultural schedules for efficient use of resources

Abstract This paper addresses a decision making problem concerning the planning of cultural schedules. The model maximizes the overall welfare of the entire system by integrating the different parties involved in the process (artistic agents, sites and administration) in a unified setting. In order to solve the proposed model this paper also derives fast ad hoc heuristics and different Lagrangian relaxations that lead to good lower and upper bounds. These bounds are later used to obtain feasible solutions that improve the currently available lower bounds. All these elements are tested over a testbed of random instances to analyze their computational performance, showing promising results. In addition, we present one particular instance based upon actual data gathered in Andalusia (Spain). The results of this analysis draw interesting conclusions on how to improve the efficient use of public funds devoted to promote cultural activities.

[1]  H. Sherali,et al.  On the choice of step size in subgradient optimization , 1981 .

[2]  Sigrid Knust,et al.  Sports league scheduling: Graph- and resource-based models , 2007 .

[3]  Justo Puerto,et al.  Dynamic supply chain design with inventory , 2008, Comput. Oper. Res..

[4]  Kevin V. Mulcahy Cultural Policy: Definitions and Theoretical Approaches , 2006 .

[5]  Efthymios Housos,et al.  An integer programming formulation for a case study in university timetabling , 2004, Eur. J. Oper. Res..

[6]  Chengbin Chu,et al.  A planning and scheduling problem for an operating theatre using an open scheduling strategy , 2010, Comput. Ind. Eng..

[7]  Timothy L. Urban,et al.  A constraint programming approach to the multiple-venue, sport-scheduling problem , 2006, Comput. Oper. Res..

[8]  G. Gallo,et al.  A multi-level bottleneck assignment approach to the bus drivers' rostering problem , 1984 .

[9]  Justo Puerto,et al.  Planning for Agricultural Forage Harvesters and Trucks: Model, Heuristics, and Case Study , 2010 .

[10]  James C. Bean,et al.  Reducing Travelling Costs and Player Fatigue in the National Basketball Association , 1980 .

[11]  Giuseppe F. Italiano,et al.  Novel Local-Search-Based Approaches to University Examination Timetabling , 2008, INFORMS J. Comput..

[12]  David W. Pentico,et al.  Assignment problems: A golden anniversary survey , 2007, Eur. J. Oper. Res..

[13]  D. Warner,et al.  A Mathematical Programming Model for Scheduling Nursing Personnel in a Hospital , 1972 .

[14]  Mauro Dell'Amico,et al.  Assignment Problems , 1998, IFIP Congress: Fundamentals - Foundations of Computer Science.

[15]  Mauro Dell'Amico,et al.  8. Quadratic Assignment Problems: Algorithms , 2009 .

[16]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988 .

[17]  Dominique de Werra,et al.  Construction of sports schedules with multiple venues , 2006, Discret. Appl. Math..

[18]  Ying Li,et al.  Hospital Operating Room Capacity Expansion , 2002, Manag. Sci..

[19]  Steven Rathgeb Smith,et al.  Mapping State Cultural Policy: The State of Washington , 2004 .

[20]  Justo Puerto,et al.  The multi-period incremental service facility location problem , 2009, Comput. Oper. Res..

[21]  Dustin Kidd,et al.  Public Culture in America: A Review of Cultural Policy Debates , 2012 .

[22]  Lori S. Franz,et al.  Scheduling Medical Residents to Rotations: Solving the Large-Scale Multiperiod Staff Assignment Problem , 1993, Oper. Res..

[23]  P. Harker,et al.  Scheduling a Major College Basketball Conference , 1998 .

[24]  Mzo Sirayi,et al.  The Concept of Arts/Cultural Management: A Critical Reflection , 2009 .