Network Models in Optimization and their Applications in Practice

Glover, Fred; Klingman, Darwin; Phillips, Nancy V.

doi:10.1002/9781118033173

Cited by 90 publications

(58 citation statements)

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“…Integer multi-commodity network flow formulations are often used in transportation problems ( [1,7]). Variable neighborhood search has proven its effectiveness on a multitude of problems.…”

Section: Literaturementioning

confidence: 99%

A Hybrid Solution Approach for Ready-Mixed Concrete Delivery

Schmid

Doerner

Hartl

et al. 2009

Transportation Science

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Companies in the concrete industry are facing the following scheduling problem on a daily basis: concrete produced at several plants has to be delivered at customers' construction sites using a heterogeneous fleet of vehicles in a timely, but cost-effective manner. As the ordered quantity of concrete typically exceeds the capacity of a single vehicle several deliveries need to be scheduled in order to fulfill an order. The deliveries cannot overlap and the time between consecutive deliveries has to be small.Our solution approach effectively integrates optimization and heuristic techniques. Information is passed back and forth between an integer multi-commodity flow optimization component and a variable neighborhood search component in order to find high-quality solutions in a reasonable amount of time. Even though both components are capable of producing feasible solutions, the integrated approach is far more effective.Computational experiments show that our hybrid method outperforms a commercially available solution approach based on simulated annealing by more than 20 percent on average.

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“…Integer multi-commodity network flow formulations are often used in transportation problems ( [1,7]). Variable neighborhood search has proven its effectiveness on a multitude of problems.…”

Section: Literaturementioning

confidence: 99%

A Hybrid Solution Approach for Ready-Mixed Concrete Delivery

Schmid

Doerner

Hartl

et al. 2009

Transportation Science

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“…Such a structure lends itself nicely to the adoption of network flow programming (Glover et al, 1992). When a situation can be entirely modelled as a network, very efficient algorithms exist for the solution of associated optimisation problems; many times more efficient than linear programming in the utilisation of computer time and memory resources (Jensen and Bard, 2002).…”

Section: Network Flow Modelmentioning

confidence: 99%

Nodal prices in an integrated energy system

Quelhas

Gil

McCalley

2006

IJCIS

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This paper presents a multiperiod generalised network flow model used to analyse the economic interdependencies of integrated energy systems comprising the electric network and the various fuel supply and delivery systems in a medium term operational time frame. By using a network flow programming model, one can take advantage of much faster solution procedures than standard linear programming techniques; an issue of importance considering the dimensionality of such integrated systems. The nodal prices that are obtained as a byproduct of the optimisation algorithm provide a way to analyse the economic interdependencies between the various fuel networks and the electric network. A numerical example is presented to highlight the benefits of the methodology and illustrate how nodal prices in the electric network are influenced by the dynamics of the various fuel networks.

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“…These systems dispense with any constraint expression language, employing instead a collection of standard symbols -such as the netforms of Glover, Klingman and Philips [15,16] [28,25,26,27], and Kendrick's PTS [30,31] can thus offer intuitive graphical interfaces for the solution of combinatorial optimization problems on networks.…”

Section: Network-based Optimizationmentioning

confidence: 99%

New constructs for the description of combinatorial optimization problems in algebraic modeling languages

Bisschop

Fourer

1996

Comput Optim Applic

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Algebraic languages are at the heart of many successful optimization modeling systems, yet they have been used with only limited success for combinatorial (or discrete) optimization. We show in this paper, through a series of examples, how an algebraic modeling language might be extended to help with a greater variety of combinatorial optimization problems. We consider specifically those problems that are readily expressed as the choice of a subset from a certain set of objects, rather than as the assignment of numerical values to variables. Since there is no practicable universal algorithm for problems of this kind, we explore a hybrid approach that employs a general-purpose subset enumeration scheme together with problem-specific directives to guide an efficient search.

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Network Models in Optimization and their Applications in Practice

Cited by 90 publications

References 0 publications

A Hybrid Solution Approach for Ready-Mixed Concrete Delivery

A Hybrid Solution Approach for Ready-Mixed Concrete Delivery

Nodal prices in an integrated energy system

New constructs for the description of combinatorial optimization problems in algebraic modeling languages

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