T.L. Magnanti and R.T. Wong. Network Design and Transportation Planning: Models and Algorithms. Transportation Science, 18:1-55, 1984.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....variables, and u and l are vectors of upper and lower bounds for the continuous variables y. The objective function f and the constraint functions g are assumed to be convex. Mixed integer non linear programs of this form arise in a number of applications, in areas as diverse as network design [13, 19], chemical process synthesis [5, 9, 16] product marketing [6] and capital budgeting [17, 20, 23] Methods for solving mixed integer nonlinear programming problems are surveyed in [10, 12] Branch and bound algorithms such as the ones described in [11, 17, 18, 22] work by explicitly enumerating ....

T.L. Magnanti and R. T. Wong, Network Design and Transportation Planning: Models and Algorithms. Transportation Science 18, 1--55 (1984).

....2 has important applications in the areas of network design and network vulnerability. In this paper we outline two of these applications. 6. 1 Heuristic for a Network Design Problem The construction of networks with specified connectivity levels between vertices has been of considerable interest [20], recently with regard to telephone system design [4, 16, 21] The version of ECAP or VCAP considered in these papers was introduced in [19] and involves instance (G; w; S; r) where the subgraph S is not connected, and the connectivity requirements are of the form r ij = minfr i ; r j g, ....

T.L. Magnanti and R.T. Wong, Network Design and transportation planning: models and algorithms, Trans. Sci. 18 (1984), 1--55.

....taille ayant jusqu a 500 sommets. Mots cl es : probl eme de chargement de r eseau, m etaheuristiques, recherche locale, diversi cation. ii 1 Introduction Network design models nd applications in various elds such as computer networks, transportation, manufacturing and telecommunications [1, 10, 20, 21]. In this paper, we study a variant of the network loading problem [19] where we have to install facilities of xed capacity on the edges of an undirected network to carry the ow from a central vertex to a set of demand vertices so that the total facility installation cost is minimized. To ....

Magnanti T.L. and R.T. Wong (1984), \Network Design and Transportation Planning: Models and Algorithms", Transportation Science 18, 1-55.

....: Probl eme de conception de r eseau avec capacit e et co ut xe, relaxation lagrangienne, m ethodes de sous gradients, m ethodes de faisceaux. ii 1 Introduction Network design models arise in various applications in telecommunications, transportation, logistics and production planning [2, 3, 16, 31, 32]. In many of these applications, the models are characterized as follows: given a network with arc capacities, it is required to send ows (which might be fractional) in order to satisfy known demands between origindestination pairs. In doing so, one pays a price not only for routing ows, but ....

Magnanti T.L., and Wong R.T. (1984), \Network Design and Transportation Planning: Models and Algorithms", Transportation Science 18(1), 1-55.

....known for long as useful planning tools in areas such as transportation, telecommunications, manufacturing and logistics, among others. Comprehensive surveys on the applications of network design models and their resolution by mathematical programming techniques can be found in Magnanti and Wong [11], and Minoux [12] In many applications, it is required to send flows (which might be fractional) to satisfy demands between multiple origin destination pairs (also called commodities) In doing so, one pays a price not only for routing flows, but also for using an arc. This is usually modeled ....

Magnanti T.L., and Wong R.T. (1984), "Network Design and Transportation Planning: Models and Algorithms", Transportation Science, 18(1), 1-55.

....are presented in Section 9. 2. The TCFA Problem in the Literature Many variants of the TCFA problem, and associated solution procedures, have appeared in the literature. Many authors assume linear cost functions and their solutions rely this feature, for example [1] 2] 8] 10] 23] [29], and [32] Hence the approaches described in these papers are not applicable to Concave TCFA problems and are not considered further in this paper. In [26] and [20] Kleinrock and Gerla assumed link cost functions to be linear or concave to reflect the effects of economies of scale in the pricing ....

T. L. Magnanti and R. T. Wong. Network design and transportation planning: Models and algorithms. Transportation Science, 18(1), (Feb. 1984) 1--55. 19

....Montreal, Quebec, Canada H3C 3J7 1 1 Introduction Network design problems are pervasive in the real world and find applications in computer networks, transportation, manufacturing and telecommunications. The early literature in this area has mostly focused on uncapacitated problems [4, 22, 24]. More recently, several authors have tackled capacitated network design problems, with either a single or a very limited number of capacity options on each link [3, 5, 6, 7, 8, 10, 11, 12, 13, 18, 19, 20, 21, 25] The capacitated problems are more di#cult to solve and raise considerable ....

Magnanti T.L. and R.T. Wong (1984), "Network Design and Transportation Planning: Models and Algorithms", Transportation Science 18, 1--55.

.... (cf. e.g. Magnanti et al. 17] 18] Holmberg and Hellstrand [13] Holmberg and Yuan [14] Balakrishnan et al. 2] Sridhar and Park [26] Lamar et al. 15] and Chang and Gavish [6] For additional references and applications see, for example, the comprehensive survey by Magnanti and Wong [19], the overview by Minoux [20] and the recent review by Crainic and Laporte [8] In contrast to that, the published literature on network design problems for airlines is scant. Actually, we are aware of no reference treating the schedule generation problem. Daskin and Panayotopoulos [10] present ....

....serve such a single ight. Essentially, we can aggregate ights if the corresponding OD pair o d is not involved in any via ight. 3. 2 Schedule Generation Model We model SGP as a capacitated network design problem with additional constraints (see Section 2, especially Magnanti and Wong [19], and Minoux [20] Compared to the general model, however, we have to observe some additional constraints: we can only introduce an arc if it is part of a feasible virtual route of an aircraft starting and ending in H. Moreover, the passenger ow between two nodes can only traverse at most two ....

T.L. Magnanti and R.T. Wong. Network design and transportation planning: Models and algorithms. Transportation Science, 18:1-55, 1984.

.... of finding optimal lines, in short line optimization, can now be performed independently on the different subnetworks like other phases of tactical railway planning [2] Possible links Figure 1: Network transformation for applying usual network design techniques In the context of network design [9, 10] the problem can be formulated as an optimum network design for minimum cost multicommodity flows. The set of possible links consists of the connections of tracks inside a station (Figure 1) If some travellers find a suitable travel path with all tracks connected by these inner links, then these ....

T.L. Magnanti and R.T. Wong. Network design and transportation planning: Models and algorithms. Transportation Sci., 18:1--55, 1984.

....avec capacit es, m ethodes de coupes, relaxation lagrangienne, optimisation non diff erentiable, calcul parall ele. ii 1 Introduction Network design models have wide applications in telecommunications and transportation planning; See, for exemple, the survey articles by Magnanti and Wong [55], Minoux [56] chapter 16 of the book by Ahuja, Magnanti and Orlin [1] section 13 of Ahuja, Magnanti, Orlin and Reddy [2] In particular, Gavish [30] and Balakrishnan, Magnanti, Shulman and Wong [8] present reviews of important applications in telecommunications. In many of these applications, it ....

....is quasi integral [44] in the sense that every edge of the convex hull of integral points is also an edge of the polytope itself. Such a property is unlikely to hold for the capacitated case. Also, it is much easier for uncapacitated problems to obtain feasible solutions with classical heuristics [55]. Another interesting special case arises when there is only one commodity. In general, the presence of capacities makes the problem difficult. In particular, Magnanti and Mirchandani [50] study the following problem, defined on an undirected graph: There are no flow costs, a single commodity ....

Magnanti T.L. and Wong R.T. (1984), Network Design and Transportation Planning: Models and Algorithms, Transportation Science, 18(1), 1-55.

....: Probl eme de conception de r eseau avec capacit e et cout fixe, relaxation lagrangienne, m ethodes de sous gradients, m ethodes de faisceaux. ii 1 Introduction Network design models arise in various applications in telecommunications, transportation, logistics and production planning [2, 3, 12, 24, 25]. In many of these applications, the models are characterized as follows: given a network with arc capacities, it is required to send flows (which might be fractional) in order to satisfy known demands between origindestination pairs. In doing so, one pays a price not only for routing flows, but ....

Magnanti T.L. and Wong R.T. (1984), "Network Design and Transportation Planning: Models and Algorithms", Transportation Science 18(1), 1--55.

....and unit capacity links the two nodes of every pair. A minimum cost flow of value 2 in this transformed network will automatically use two node disjoint paths. Problem (UDBR) is an extension to two paths by commodity of the well known uncapacitated network design problem (UNDP ) Magnanti and Wong [MW84] review the formulations of (UNDP ) and show that this problem contains several well known special cases. They also describe existing optimization methods yelding lower bounds and optimal solutions and compare the performance of several heuristics. Balakrishnan et al. BMW89] propose two ....

T.L. Magnanti and R.T. Wong. Network design and transportation planning: Models and algorithms. Transportation Science, 18:1--55, 1984.

....Graduate Fellowship, Air Force contract F49620 92 J 0125, and DARPA contract N00014 92 J 1799. This research was done while a graduate student at MIT. 1 Introduction Network design problems have a wide range of practical applications, ranging from telecommunications to transportation problems [10]. In this paper, we will investigate approximation algorithms for several basic network design problems. In a network design problem, the input consists of an undirected graph G = V; E) where each edge e 2 E has a nonnegative cost c(e) and we wish to select a minimumcost subgraph that ....

T. L. Magnanti and R. T. Wong. Network design and transportation planning: Models and algorithms. Transportation Science, 18:1--55, 1984.

No context found.

T.L. Magnanti and R.T. Wong. Network Design and Transportation Planning: Models and Algorithms. Transportation Science, 18:1-55, 1984.

No context found.

T. L. Magnanti and R. T. Wong. Network design and transportation planning: Models and algorithms. Transportation Science, 18(1):1--55, 1984.

No context found.

Magnanti, T.L. and Wong, R.T. (1986). Network Design and Transportation Planning: Models and Algorithms Transportation Science, 18(1): 1-55

No context found.

T.L. Magnanti and R.T. Wong. Network design and transportation planning: Models and algorithms. Transportation Sci., 18:1--55, 1984.

No context found.

T. L. Magnanti and R. T. Wong. Network design and transportation planning: Models and algorithms. Transportation Science, 18:1--55, 1984.

No context found.

T. L. Magnanti and R. T. Wong. Network design and transportation planning: Models and algorithms. Transportation Science, 18(1):1--55, 1984.

No context found.

T. L. Magnanti and R. T. Wong. Network design and transportation planning: Models and algorithms. Transportation Science, 18(1):1--55, 1984.

No context found.

T. L. Magnanti and R. T. Wong. Network design and transportation planning: Models and algorithms. Transportation Science, 18(1):1--55, 1984.

No context found.

T.L. Magnanti and R.T. Wong. Network design and transportation planning: Models and algorithms. Transportation Science, 18(1):1--55, 1984.

No context found.

Magnanti, T.L., R.T. Wong. 1984. Network Design and Transportation Planning: Models and Algorithms. Transportation Science 18, 1--55.

No context found.

T.L. Magnanti and R.T. Wong. Network design and transportation planning: Models and algorithms. Transportation Sci., 18:1--55, 1984.

No context found.

Maganati, T.L. and Wong, R.T., Network Design and Transportation Planning: Models and Algorithms. Transportation Science, Vol. 18, 1-55.

First 50 documents

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC