Multi-objective discrete urban road network design

Miandoabchi, Elnaz; Daneshzand, Farzaneh; Szeto, W.Y.; Farahani, Reza Zanjirani

doi:10.1016/j.cor.2013.03.016

Cited by 49 publications

(37 citation statements)

References 70 publications

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“…So, using values of this variable, the path for each member is determined. Expression (1) (assuring that when the existing population in any arc k − l, due to traveling members from different demand nodes, is more than a determined coefficient of its capacity, then is to be 1, otherwise zero), is captured by constraints (14) and (15). Similarly, expression (2) has been transformed into constraints Eqs.…”

Section: Model Formulationmentioning

confidence: 99%

“…They proposed a hybrid genetic algorithm and an evolutionary simulated annealing algorithm to solve the proposed model. Later, the authors of [15] considered the same problem in a multi-objective decision-making framework. They formulated the problem as a mixed-integer non-linear programming model with equilibrium constraints and presented three meta-heuristic algorithms for solving the problem.…”

Section: Introductionmentioning

confidence: 97%

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Planning a Capacitated Road Network with Flexible Travel Times: A Genetic Algorithm

2015

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We are concerned with a capacitated location-multi allocation-routing problem in a road network with flexible travel times. It is assumed that all links are two-way and capacities of the server nodes and arcs for accepting of population are limited. The aim of our work is to find numbers and locations of server nodes, allocation of the existing population in existing demand nodes on the network to the servers and the allocation of existing population in each node to different routes to determine the decided server for each member so that total transportation time is minimized. Here, two basic concepts are considered: multi allocation and flexible travel times. The concept of multi allocation arises from the possibility of allocating the existing population in a demand node to more than one server node. Also, flexible travel times concentrate on impact of traveling population on the times of links simultaneously, that is, depending on how the population is distributed on the network, the travel times on links may be increased. So, to have the least increase in the time of each link, it is necessary to decide upon the distribution of population in the network. We formulate the proposed problem as a mixed-integer nonlinear programming model and then present a genetic algorithm (GA) for solving large problems Finally, we make two sets of numerical experiments and analyze the obtained results by LINGO solver and GA. Numerical results show the proposed GA to be highly efficient.

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Section: Model Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Planning a Capacitated Road Network with Flexible Travel Times: A Genetic Algorithm

2015

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“…The decision variables are typically discrete in nature (as also shown by Miandoabchi et al, 2013;Wang et al, 2013), the design problems are often cast in various forms of integer or mixed integer programming models with NP-hard complexity. Many integer programming solution approaches have been developed along this research line.…”

Section: Network Design and Accessibilitymentioning

confidence: 99%

Transportation network design for maximizing space–time accessibility

Zhou

Miller

2015

Transportation Research Part B: Methodological

134

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a b s t r a c tOne of the goals of transportation system construction and management is to improve individuals' accessibility or the ease of reaching desired activities, destinations and services. However, many transportation network design models instead focus on maximizing individuals' mobility or the ease of movement within the network. By adapting a space-time prism analysis framework, this paper aims to address a new urban network design problem to maximize the system-wide transportation accessibility between major activity locations, subject to a given highway construction budget. By constructing a time-dependent space-time network, we formulate the problem as a linear integer programming model to maximize the number of accessible activity locations within travel time budget for road users. A Lagrangian relaxation solution framework effectively decomposes the original complex problem into classical subproblems such as knapsack and time-dependent least cost problems. Various examples and discussions are provided to consider the effectiveness of the proposed method in modeling accessibility-enhancement strategies such as congestion mitigation and land use policies.

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“…An observation found in the current NDP literature is that the combination of two or more strategic and tactical decisions has been addressed in a number of DNDPs and MNDPs (eg, Miandoabchi and Farahani, 2011;Miandoabchi et al, 2012Miandoabchi et al, , 2013. These decisions have been modelled in the form of conventional single time period models.…”

Section: Introductionmentioning

confidence: 99%

Time-dependent discrete road network design with both tactical and strategic decisions

Miandoabchi¹,

Daneshzand

Farahani

et al. 2015

Journal of the Operational Research Society

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This paper aims to model and investigate the discrete urban road network design problem, using a multi-objective time-dependent decision-making approach. Given a base network made up with two-way links, candidate link expansion projects, and candidate link construction projects, the problem determines the optimal combination of one-way and two-way links, the optimal selection of capacity expansion projects, and the optimal lane allocations on two-way links over a dual time scale. The problem considers both the total travel time and the total CO emissions as the two objective function measures. The problem is modelled using a time-dependent approach that considers a planning horizon of multiple years and both morning and evening peaks. Under this approach, the model allows determining the sequence of link construction, the expansion projects over a predetermined planning horizon, the configuration of street orientations, and the lane allocations for morning and evening peaks in each year of the planning horizon. This model is formulated as a mixed-integer programming problem with mathematical equilibrium constraints. In this regard, two multi-objective metaheuristics, including a modified nondominated sorting genetic algorithm (NSGA-II) and a multi-objective B-cell algorithm, are proposed to solve the above-mentioned problem. Computational results for various test networks are also presented in this paper.

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Multi-objective discrete urban road network design

Cited by 49 publications

References 70 publications

Planning a Capacitated Road Network with Flexible Travel Times: A Genetic Algorithm

Planning a Capacitated Road Network with Flexible Travel Times: A Genetic Algorithm

Transportation network design for maximizing space–time accessibility

Time-dependent discrete road network design with both tactical and strategic decisions

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