New Mixed Integer Programming for Facility Layout Design without Loss of Department Area

This paper proposes a New Mixed Integer Programming (NMIP) for solving facility layout problem (FLP). The formulation is extensively tested on problems from literature to minimize material handling cost when addresses on the shop floor. Every department and shop floor in tested problem were fixed dimension of length and width. Classic Mixed Integer Programming (MIP) solves FLP with fixed layout area and preset each department’s lower-upper limit of length and width. As a result, there might be some departments with 5-10% area less than initial layout design requirements which leads to problem in design and construction process. It is infeasible to address the department on the actual shop floor thus adjustment of result from MIP is required. The main purpose of NMIP is to eliminate such infeasibility and show the efficiency of this model. Keywords: mixed integer programing, facility layout design, facility layout problem, heuristics

[1]  Benoit Montreuil,et al.  A Modelling Framework for Integrating Layout Design and flow Network Design , 1991 .

[2]  N. Jawahar,et al.  A new iterated fast local search heuristic for solving QAP formulation in facility layout design , 2009 .

[3]  Ruddell Reed,et al.  An applied model for the facilities design problem , 1976 .

[4]  T. Koopmans,et al.  Assignment Problems and the Location of Economic Activities , 1957 .

[5]  Elwood S. Buffa,et al.  A Heuristic Algorithm and Simulation Approach to Relative Location of Facilities , 1963 .

[6]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.

[7]  Mitsuo Gen,et al.  Genetic algorithms and engineering optimization , 1999 .

[8]  Henri Pierreval,et al.  Evolutionary approaches to the design and organization of manufacturing systems , 2003 .

[9]  Surya Prakash Singh,et al.  Solving Facility Layout Problem: Three-level Tabu Search Metaheuristic Approach , 2009 .

[10]  Phen Chiak See,et al.  Application of ant colony optimisation algorithms in solving facility layout problems formulated as quadratic assignment problems: a review , 2008 .

[11]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[12]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[13]  Leon F. McGinnis Material handling research colloquium , 1989 .

[14]  Pranab K. Dan,et al.  Metaheuristic in facility layout problems: current trend and future direction , 2012 .

[15]  Chun Hung Cheng,et al.  Dynamic layout algorithms: a state-of-the-art survey , 1998 .

[16]  N. Jawahar,et al.  A population-based hybrid ant system for quadratic assignment formulations in facility layout design , 2009 .

[17]  Abdullah Konak,et al.  A new mixed integer programming formulation for facility layout design using flexible bays , 2006, Oper. Res. Lett..

[18]  Gilbert Laporte,et al.  Loop based facility planning and material handling , 2002, Eur. J. Oper. Res..

[19]  Kyrre Glette,et al.  Adaptive variable neighborhood search for solving multi-objective facility layout problems with unequal area facilities , 2013, Swarm Evol. Comput..

[20]  E. Ralph Sims,et al.  Planning and Managing Industrial Logistics Systems , 1991 .

[21]  George Ioannou,et al.  An integrated model and a decomposition-based approach for concurrent layout and material handling system design , 2007, Comput. Ind. Eng..