Optimization of Water Distribution Systems by a Tabu Search Metaheuristic

A Tabu Search optimisation technique is proposed for designing, planning and maintaining water distribution systems. As design and maintenance of pipe networks for water supply distribution require high costs, achieving the highest level of performance of existing networks at minimum costs is mandatory. The problem involves setting a lot of variables, as location and diameters of new pipes, operations on existing pipes, and so on. The domain of variables is discrete in nature, due to the fact that pipes are available with unified dimensions. Furthermore, the objective function to be minimised, i.e., the total cost of the plant, is non linear, non differentiable, highly ill-conditioned, and presents a huge amount of local minima. Recently, increasing attention has been paid to heuristic optimisation techniques, such as genetic algorithms (GA), simulated annealing (SA), and tabu-search (TS) for large combinatorial optimisation problems. In particular, GA has been applied to the problem of designing and maintaining water distribution networks. Results show good performance of the GA in terms of objective function values, but high computation time. One of the most promising approaches to combinatorial optimisation problems is the TS metaheuristic, that showed flexibility and effectiveness in a lot of applications. The aim of this paper is to present a TS based algorithm to the design of water distribution systems, and to demonstrate its validity in this field.

[1]  Godfrey A. Walters,et al.  A Review of Pipe Network Optimization Techniques , 1992 .

[2]  Angus R. Simpson,et al.  Optimisation of large-scale water distribution system design using genetic algorithms , 1998 .

[3]  Manoj Kumar OPTIMIZATION USING GENETIC ALGORITHMS , 1998 .

[4]  Roberto Battiti,et al.  The Reactive Tabu Search , 1994, INFORMS J. Comput..

[5]  Robert J. Vanderbei,et al.  Commentary - Interior-Point Methods: Algorithms and Formulations , 1994, INFORMS J. Comput..

[6]  Angus R. Simpson,et al.  Genetic algorithms compared to other techniques for pipe optimization , 1994 .

[7]  A. Simpson,et al.  An Improved Genetic Algorithm for Pipe Network Optimization , 1996 .

[8]  John J. Grefenstette,et al.  A Parallel Genetic Algorithm , 1987, ICGA.

[9]  Johannes Gessler Pipe Network Optimization by Enumeration , 1985 .

[10]  A. Cenedese,et al.  Optimal design of water distribution networks , 1978 .

[11]  Alfred V. Aho,et al.  Data Structures and Algorithms , 1983 .

[12]  U. Shamir,et al.  Reply [to “Comment on ‘Design of optimal water distribution systems’ by E. Alperovits and U. Shamir”] , 1979 .

[13]  Linus Schrage,et al.  Modeling and Optimization With Gino , 1986 .

[14]  Robert Sedgewick,et al.  Algorithms in C , 1990 .

[15]  C. Reeves Modern heuristic techniques for combinatorial problems , 1993 .

[16]  A. Ben-Tal,et al.  Optimal design of water distribution networks , 1994 .

[17]  Aharon Ben-Tal,et al.  Global minimization by reducing the duality gap , 1994, Math. Program..

[18]  James P. Heaney,et al.  Robust Water System Design with Commercial Intelligent Search Optimizers , 1999 .

[19]  U. Shamir,et al.  Design of optimal water distribution systems , 1977 .

[20]  D. B. Khang,et al.  A two‐phase decomposition method for optimal design of looped water distribution networks , 1990 .

[21]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[22]  Graeme C. Dandy,et al.  A Review of Pipe Network Optimisation Techniques , 1993 .

[23]  Graeme C. Dandy,et al.  Genetic algorithms compared to other techniques for pipe optimization , 1994 .

[24]  U. Shamir,et al.  Analysis of the linear programming gradient method for optimal design of water supply networks , 1989 .