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  • A tabu search for the design of capacitated rooted survivable planar networks
    J. Heuristics (IF 1.577) Pub Date : 2020-07-27
    Alain Hertz, Thomas Ridremont

    Consider a rooted directed graph G with a subset of vertices called terminals, where each arc has a positive integer capacity and a non-negative cost. For a given positive integer k, we say that G is k-survivable if every of its subgraphs obtained by removing at most k arcs admits a feasible flow that routes one unit of flow from the root to every terminal. We aim at determining a k-survivable subgraph

  • A genetic algorithm for finding realistic sea routes considering the weather
    J. Heuristics (IF 1.577) Pub Date : 2020-07-23
    Stefan Kuhlemann, Kevin Tierney

    The weather has a major impact on the profitability, safety, and environmental sustainability of the routes sailed by seagoing vessels. The prevailing weather strongly influences the course of routes, affecting not only the safety of the crew, but also the fuel consumption and therefore the emissions of the vessel. Effective decision support is required to plan the route and the speed of the vessel

  • Evolutionary multi-level acyclic graph partitioning
    J. Heuristics (IF 1.577) Pub Date : 2020-07-15
    Orlando Moreira, Merten Popp, Christian Schulz

    Directed graphs are widely used to model data flow and execution dependencies in streaming applications. This enables the utilization of graph partitioning algorithms for the problem of parallelizing execution on multiprocessor architectures under hardware resource constraints. However due to program memory restrictions in embedded multiprocessor systems, applications need to be divided into parts

  • A multi-start local search algorithm for the Hamiltonian completion problem on undirected graphs
    J. Heuristics (IF 1.577) Pub Date : 2020-07-01
    Jorik Jooken, Pieter Leyman, Patrick De Causmaecker

    This paper proposes a local search algorithm for a specific combinatorial optimisation problem in graph theory: the Hamiltonian completion problem (HCP) on undirected graphs. In this problem, the objective is to add as few edges as possible to a given undirected graph in order to obtain a Hamiltonian graph. This problem has mainly been studied in the context of various specific kinds of undirected

  • Distance-guided local search
    J. Heuristics (IF 1.577) Pub Date : 2020-05-26
    Daniel Porumbel, Jin-Kao Hao

    We present several techniques that use distances between candidate solutions to achieve intensification in Local Search (LS) algorithms. An important drawback of classical LS is that after visiting a very high-quality solution the search process can “forget about it” and continue towards very different areas. We propose a method that works on top of a given LS to equip it with a form of memory so as

  • IoT networks 3D deployment using hybrid many-objective optimization algorithms
    J. Heuristics (IF 1.577) Pub Date : 2020-05-18
    Sami Mnasri, Nejah Nasri, Malek Alrashidi, Adrien van den Bossche, Thierry Val

    When resolving many-objective problems, multi-objective optimization algorithms encounter several difficulties degrading their performances. These difficulties may concern the exponential execution time, the effectiveness of the mutation and recombination operators or finding the tradeoff between diversity and convergence. In this paper, the issue of 3D redeploying in indoor the connected objects (or

  • Basic variable neighborhood search for the minimum sitting arrangement problem
    J. Heuristics (IF 1.577) Pub Date : 2020-01-13
    Eduardo G. Pardo, Antonio García-Sánchez, Marc Sevaux, Abraham Duarte

    The minimum sitting arrangement (MinSA) problem is a linear layout problem consisting in minimizing the number of errors produced when a signed graph is embedded into a line. This problem has been previously tackled by theoretical and heuristic approaches in the literature. In this paper we present a basic variable neighborhood search (BVNS) algorithm for solving the problem. First, we introduce a

  • Logistics optimization for a coal supply chain
    J. Heuristics (IF 1.577) Pub Date : 2020-01-14
    Gleb Belov, Natashia L. Boland, Martin W. P. Savelsbergh, Peter J. Stuckey

    The Hunter Valley coal export supply chain in New South Wales, Australia, is of great importance to the Australian economy. Effectively managing its logistics, however, is challenging, because it is a complex system, covering a large geographic area and comprising a rail network, three coal terminals, and a port, and has many stakeholders, e.g., mining companies, port authorities, coal terminal operators

  • Bilevel optimization based on iterative approximation of multiple mappings
    J. Heuristics (IF 1.577) Pub Date : 2019-09-24
    Ankur Sinha, Zhichao Lu, Kalyanmoy Deb, Pekka Malo

    A large number of application problems involve two levels of optimization, where one optimization task is nested inside the other. These problems are known as bilevel optimization problems and have been studied by both classical optimization community and evolutionary optimization community. Most of the solution procedures proposed until now are either computationally very expensive or applicable to

  • Enhancement for human resource management in the ULD build-up process of air-cargo terminal: a strategic linkage approach
    J. Heuristics (IF 1.577) Pub Date : 2020-01-21
    Hyun Jun Yang, Suk Jae Jeong, Sung Wook Yoon

    This study proposes a strategic linkage method with mathematical model, simulation model and heuristic approaches to an adaptive workforce scheduling problem reflecting the work site situation of the air cargo terminal. For the application of the proposed method, we first generate an initial workforce schedule using the optimization model for minimizing labor costs. The simulation model is then used

  • Heuristics for a vehicle routing problem with information collection in wireless networks
    J. Heuristics (IF 1.577) Pub Date : 2019-10-24
    Luis Flores-Luyo, Agostinho Agra, Rosa Figueiredo, Eladio Ocaña

    We consider a wireless network where a given set of stations is continuously generating information. A single vehicle, located at a base station, is available to collect the information via wireless transfer. The wireless transfer vehicle routing problem (WTVRP) is to decide which stations should be visited in the vehicle route, how long shall the vehicle stay in each station, and how much information

  • A hybrid genetic algorithm for the traveling salesman problem with drone
    J. Heuristics (IF 1.577) Pub Date : 2019-11-13
    Quang Minh Ha, Yves Deville, Quang Dung Pham, Minh Hoàng Hà

    This paper addresses the traveling salesman problem with drone (TSP-D), in which a truck and drone are used to deliver parcels to customers. The objective of this problem is to either minimize the total operational cost (min-cost TSP-D) or minimize the completion time for the truck and drone (min-time TSP-D). This problem has gained a lot of attention in the last few years reflecting the recent trends

  • Heuristic/meta-heuristic methods for restricted bin packing problem
    J. Heuristics (IF 1.577) Pub Date : 2020-03-30
    Yu Fu, Amarnath Banerjee

    This paper addresses a special bin packing problem in which each item can only be assigned to a subset of the bins. We name this problem as the restricted bin packing problem (RBPP). This paper is designed to explore the relationships of RBPP with classic NP-complete problems, and to resolve the restrictions of assignment through heuristic and meta-heuristic algorithms. A new heuristic algorithm named

  • Meta-heuristics for the one-dimensional cutting stock problem with usable leftover
    J. Heuristics (IF 1.577) Pub Date : 2020-03-03
    Santiago V. Ravelo, Cláudio N. Meneses, Maristela O. Santos

    This work considers the one-dimensional cutting stock problem in which the non-used material in the cutting patterns may be used in the future, if large enough. We show that a multiobjective criteria to classify the solutions could be more accurate than previous classifications attempts, also we give a heuristic algorithm and two meta-heuristic approaches to the problem and we use them to solve practical

  • Pareto-based evolutionary multiobjective approaches and the generalized Nash equilibrium problem
    J. Heuristics (IF 1.577) Pub Date : 2020-02-14
    Rodica Ioana Lung, Noémi Gaskó, Mihai Alexandru Suciu

    Pareto-based evolutionary multiobjective approaches are methods that use the Pareto dominance concept to guide the search of evolutionary algorithms towards the Pareto frontier of a problem. To address the challenge of providing an entire set of optimal solutions they use specially designed mechanisms for preserving search diversity and maintaining the non-dominated solutions set. The limitation of

  • Heuristic solutions to robust variants of the minimum-cost integer flow problem
    J. Heuristics (IF 1.577) Pub Date : 2020-02-14
    Marko Špoljarec, Robert Manger

    This paper deals with robust optimization applied to network flows. We consider two robust variants of the minimum-cost integer flow problem. Thereby, uncertainty in problem formulation is limited to arc costs and expressed by a finite set of explicitly given scenarios. It turns out that both problem variants are NP-hard. To solve the considered variants, we propose several heuristics based on local

  • An automatic constructive matheuristic for the shift minimization personnel task scheduling problem
    J. Heuristics (IF 1.577) Pub Date : 2020-02-13
    Reshma Chirayil Chandrasekharan, Pieter Smet, Tony Wauters

    The shift minimization personnel task scheduling problem is an NP-complete optimization problem that concerns the assignment of tasks to multi-skilled employees with a view to minimize the total number of assigned employees. Recent literature indicates that hybrid methods which combine exact and heuristic techniques such as matheuristics are efficient as regards to generating high quality solutions

  • New heuristic algorithms for the Dubins traveling salesman problem
    J. Heuristics (IF 1.577) Pub Date : 2020-02-13
    Luitpold Babel

    The problem of finding a shortest curvature-constrained closed path through a set of targets in the plane is known as Dubins traveling salesman problem (DTSP). Applications of the DTSP include motion planning for kinematically constrained mobile robots and unmanned fixed-wing aerial vehicles. The difficulty of the DTSP is to simultaneously find an order of the targets and suitable headings (orientation

  • MIP neighborhood search heuristics for a service network design problem with design-balanced requirements
    J. Heuristics (IF 1.577) Pub Date : 2020-02-04
    Naoto Katayama

    Service network design problems are used to address a variety of services in transportation and logistics planning. In the present paper, we consider the service network design problem with design-balanced requirements. This problem is particularly relevant to operations for consolidation transportation systems and determines the transportation network configuration and the characteristics of the corresponding

  • A comparative study of multi-objective machine reassignment algorithms for data centres
    J. Heuristics (IF 1.577) Pub Date : 2019-09-20
    Takfarinas Saber, Xavier Gandibleux, Michael O’Neill, Liam Murphy, Anthony Ventresque

    At a high level, data centres are large IT facilities hosting physical machines (servers) that often run a large number of virtual machines (VMs)—but at a lower level, data centres are an intricate collection of interconnected and virtualised computers, connected services, complex service-level agreements. While data centre managers know that reassigning VMs to the servers that would best serve them

  • A coordinated production and transportation scheduling problem with minimum sum of order delivery times
    J. Heuristics (IF 1.577) Pub Date : 2019-07-25
    Ling Liu, Wenli Li, Kunpeng Li, Xuxia Zou

    In this paper, a coordinated production scheduling and vehicle routing problem aiming at minimizing the sum of order delivery times is considered, where there are a single machine for production and limited number of homogenous capacitated vehicles for transportation. Given the complexity of the studied problem, a variable neighborhood search (VNS) algorithm is proposed to address this problem. To

  • Objective scaling ensemble approach for integer linear programming
    J. Heuristics (IF 1.577) Pub Date : 2019-06-29
    Weili Zhang, Charles D. Nicholson

    The objective scaling ensemble approach is a novel two-phase heuristic for integer linear programming problems shown to be effective on a wide variety of integer linear programming problems. The technique identifies and aggregates multiple partial solutions to modify the problem formulation and significantly reduce the search space. An empirical analysis on publicly available benchmark problems demonstrate

  • MIQP model and improvement heuristic for power loss minimization in distribution system with network reconfiguration
    J. Heuristics (IF 1.577) Pub Date : 2019-08-01
    Karla B. Freitas, Márcio S. Arantes, Claudio F. M. Toledo, Alexandre C. B. Delbem

    The problem of reconfiguration in electrical power distribution systems deals with changes in the network topology using maneuvers switches. This is an optimization problem where one of the goals is to minimize losses following constraints such as faults isolation, load feeders balancing and voltage profile improvement. The present paper solves such problem by introducing a mixed-integer quadratic

  • Hybrid adaptive large neighborhood search algorithm for the mixed fleet heterogeneous dial-a-ride problem
    J. Heuristics (IF 1.577) Pub Date : 2019-09-09
    Mohamed Amine Masmoudi, Manar Hosny, Emrah Demir, Erwin Pesch

    The mixed fleet heterogeneous dial-a-ride problem (MF-HDARP) consists of designing vehicle routes for a set of users by using a mixed fleet including both heterogeneous conventional and alternative fuel vehicles. In addition, a vehicle is allowed to refuel from a fuel station to eliminate the risk of running out of fuel during its service. We propose an efficient hybrid adaptive large neighborhood

  • A heuristic for fair dynamic resource allocation in overloaded OFDMA systems
    J. Heuristics (IF 1.577) Pub Date : 2019-07-22
    Adam N. Letchford, Qiang Ni, Zhaoyu Zhong

    OFDMA is a popular coding scheme for mobile wireless communications. In OFDMA, one must allocate the available resources (bandwidth and power) dynamically, as user requests arrive and depart in a stochastic manner. Several exact and heuristic methods exist to do this, but they all perform poorly in the “over-loaded” case, in which the user demand is close to or exceeds the system capacity. To address

  • On combining variable ordering heuristics for constraint satisfaction problems
    J. Heuristics (IF 1.577) Pub Date : 2020-01-21
    Hongbo Li, Guozhong Feng, Minghao Yin

    Variable ordering heuristics play a central role in solving constraint satisfaction problems. Combining two variable ordering heuristics may generate a more efficient heuristic, such as dom/deg. In this paper, we propose a novel method for combining two variable ordering heuristics, namely Pearson-Correlation-Coefficient-based Combination (PCCC). While the existing combination strategies always combine

  • The selective traveling salesman problem with draft limits
    J. Heuristics (IF 1.577) Pub Date : 2019-01-29
    Shahin Gelareh, Bernard Gendron, Saïd Hanafi, Rahimeh Neamatian Monemi, Raca Todosijević

    This paper introduces the selective traveling salesman problem with draft limits, an extension of the traveling salesman problem with draft limits, wherein the goal is to design a maximum profit tour respecting draft limit constraints at the visited nodes. We propose a mixed integer linear programming (MILP) formulation for this problem. This MILP model is used to solve—to optimality—small size instances

  • A biased-randomized variable neighborhood search for sustainable multi-depot vehicle routing problems
    J. Heuristics (IF 1.577) Pub Date : 2018-02-27
    Lorena Reyes-Rubiano, Laura Calvet, Angel A. Juan, Javier Faulin, Lluc Bové

    Urban freight transport is becoming increasingly complex due to a boost in the volume of products distributed and the associated number of delivery services. In addition, stakeholders’ preferences and city logistics dynamics affect the freight flow and the efficiency of the delivery process in downtown areas. In general, transport activities have a significant and negative impact on the environment

  • A variable neighborhood search simheuristic for project portfolio selection under uncertainty
    J. Heuristics (IF 1.577) Pub Date : 2018-02-24
    Javier Panadero, Jana Doering, Renatas Kizys, Angel A. Juan, Angels Fito

    With limited financial resources, decision-makers in firms and governments face the task of selecting the best portfolio of projects to invest in. As the pool of project proposals increases and more realistic constraints are considered, the problem becomes NP-hard. Thus, metaheuristics have been employed for solving large instances of the project portfolio selection problem (PPSP). However, most of

  • The parking allocation problem for connected vehicles
    J. Heuristics (IF 1.577) Pub Date : 2018-01-03
    Marko Mladenović, Thierry Delot, Gilbert Laporte, Christophe Wilbaut

    In this paper, we propose a parking allocation model that takes into account the basic constraints and objectives of a problem where parking lots are assigned to vehicles. We assume vehicles are connected and can exchange information with a central intelligence. Vehicle arrival times can be provided by a GPS device, and the estimated number of available parking slots, at each future time moment and

  • A general variable neighborhood search for solving the multi-objective open vehicle routing problem
    J. Heuristics (IF 1.577) Pub Date : 2017-12-23
    Jesús Sánchez-Oro, Ana D. López-Sánchez, J. Manuel Colmenar

    The multi-objective open vehicle routing problem (MO-OVRP) is a variant of the classic vehicle routing problem in which routes are not required to return to the depot after completing their service and where more than one objective is optimized. This work is intended to solve a more realistic and general version of the problem by considering three different objective functions. MO-OVRP seeks solutions

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