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Solving Optimisation Problems with Catamorphisms

by Richard Bird, Oege De Moor , 1992
"... . This paper contributes to an ongoing effort to construct a calculus for deriving programs for optimisation problems. The calculus is built around the notion of initial data types and catamorphisms which are homomorphisms on initial data types. It is shown how certain optimisation problems, which a ..."
Abstract - Cited by 12 (3 self) - Add to MetaCart
. This paper contributes to an ongoing effort to construct a calculus for deriving programs for optimisation problems. The calculus is built around the notion of initial data types and catamorphisms which are homomorphisms on initial data types. It is shown how certain optimisation problems, which

Some optimisation problems revisited

by Henry B. Mcloughlin, Kevin Hely
"... We consider some simple optimisation problems and employ a non-traditional method to solve them. We try to model both the problem and solution domains as algebraic structures, attempting to characterise the join operations on these domains. In each of the examples chosen, these structures turn out t ..."
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We consider some simple optimisation problems and employ a non-traditional method to solve them. We try to model both the problem and solution domains as algebraic structures, attempting to characterise the join operations on these domains. In each of the examples chosen, these structures turn out

On the Hardness of Decision and Optimisation Problems

by John Slaney, Sylvie Thiébaux , 1998
"... . Recent work on phase transition has detected apparently interesting phenomena in the distribution of hard optimisation problems (find, on some measure, the least m such that the given instance x has a solution of value m) and their corresponding decision problems (determine, for a given bound m wh ..."
Abstract - Cited by 10 (5 self) - Add to MetaCart
. Recent work on phase transition has detected apparently interesting phenomena in the distribution of hard optimisation problems (find, on some measure, the least m such that the given instance x has a solution of value m) and their corresponding decision problems (determine, for a given bound m

Multilevel Refinement for Combinatorial Optimisation Problems

by Chris Walshaw - SE10 9LS , 2001
"... Abstract. We consider the multilevel paradigm and its potential to aid the solution of combinatorial optimisation problems. The multilevel paradigm is a simple one, which involves recursive coarsening to create a hierarchy of approximations to the original problem. An initial solution is found (some ..."
Abstract - Cited by 54 (5 self) - Add to MetaCart
Abstract. We consider the multilevel paradigm and its potential to aid the solution of combinatorial optimisation problems. The multilevel paradigm is a simple one, which involves recursive coarsening to create a hierarchy of approximations to the original problem. An initial solution is found

A Unified Model of Optimisation Problems

by Cristina C. Vieira, Carlos M. Fonseca
"... In this work, a conceptual software model of optimisation problems is developed. Problem-specific aspects are clearly identified as such. To achieve the desired separation between problems and solvers, the details of the problem are encapsulated, and mechanisms capable of supporting the optimisation ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
In this work, a conceptual software model of optimisation problems is developed. Problem-specific aspects are clearly identified as such. To achieve the desired separation between problems and solvers, the details of the problem are encapsulated, and mechanisms capable of supporting

Uncertain Constraint Optimisation Problems

by Neil Yorke-smith, Carmen Gervet
"... Abstract Data uncertainties are inherent in the real world. The uncertain CSP (UCSP) is an extension of classical CSP that models incomplete and erroneous data by coefficients in the constraints whose values are unknown but bounded, for instance by an interval. It resolution is a closure, a set of p ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
of potential solutions. This paper extends the UCSP model to account for optimisation criteria, by defining the uncertain CSOP. The challenge is to combine optimisation (preferences over individual solutions) with a closure of a certain type (preference over sets of solutions) to a UCSOP. Unlike traditional

Portfolio Optimisation Problems

by R.S. Womersley, K. Lau, Then Satisfies , 1996
"... . More generally there may be simple lower and upper bounds # i # x i # u i i = 1, . . . , n (1.1) on the weights (e.g. the fraction of the portfolio in property must be between 5% and 20%), and general linear constraints # n+i # a T i x # u n+i i = 1, . . . , m. (e.g. the total fractio ..."
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. More generally there may be simple lower and upper bounds # i # x i # u i i = 1, . . . , n (1.1) on the weights (e.g. the fraction of the portfolio in property must be between 5% and 20%), and general linear constraints # n+i # a T i x # u n+i i = 1, . . . , m. (e.g. the total fraction of the portfolio allocated to all international assets must not exceed 40%). Writing the constant vectors a i # R n as the rows of the matrix A # R mn defined by A T = [a 1 am ] the linear constraints are # # # x Ax # # u, (1.2) where # #<F11.

in dose optimisation problems.

by unknown authors
"... Advantages of combining gamma scanning techniques and 3D dose simulation ..."
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Advantages of combining gamma scanning techniques and 3D dose simulation

NONITERATIVE COORDINATION APPLICATION IN SOLVING PORTFOLIO OPTIMISATION PROBLEMS

by K. Stoilova T. Stoilov
"... Abstract: Hierarchical approach is applied for solving portfolio optimisation problem. It is solved without subject determination of the preferable coefficient. Here it is determined as a decision of optimisation problem, solved at the upper level of an hierarchical system. This methodology allows ..."
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Abstract: Hierarchical approach is applied for solving portfolio optimisation problem. It is solved without subject determination of the preferable coefficient. Here it is determined as a decision of optimisation problem, solved at the upper level of an hierarchical system. This methodology allows

On the use of CBR in optimisation problems such as the TSP

by Padraig Cunningham, Barry Smyth, Neil Hu , 1995
"... The particular strength of CBR is normally considered to be its use in weak theory domains where solution quality is compiled into cases and is reusable. In this paper we explore an alternative use of CBR in optimisation problems where cases represent highly optimised structures in a huge highly ..."
Abstract - Cited by 4 (2 self) - Add to MetaCart
The particular strength of CBR is normally considered to be its use in weak theory domains where solution quality is compiled into cases and is reusable. In this paper we explore an alternative use of CBR in optimisation problems where cases represent highly optimised structures in a huge highly
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