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The circular economy is gaining in importance globally and locally. The COVID-19 crisis, as an exceptional event, showed the limits and the fragility of supply chains, with circular economy practices as a potential solution during and post-COVID. Reverse logistics (RL) is an important dimension of the circular economy which allows management of economic, social, and environmental challenges. Transportation is needed for RL to effectively operate, but research study on this topic has been relatively limited. New digitalization opportunities can enhance transportation and RL, and therefore further enhance the circular economy. This paper proposes to review practical research and concerns at the nexus of transportation, RL, and blockchain as a digitalizing technology. The potential benefits of blockchain technology through example use cases on various aspects of RL and transportation activities are presented. This integration and applications are evaluated using various capability facets of blockchain technology, particularly as an immutable and reliable ledger, a tracking service, a smart contract utility, as marketplace support, and as tokenization and incentivization. We also briefly introduce the physical internet concept within this context. The physical internet paradigm proposed last decade, promises to also disrupt the blockchain, transportation, and RL nexus. We include potential research directions and managerial implications across the blockchain, transportation, and RL nexus.
Abdelghani Bekrar; Abdessamad Ait El Cadi; Raca Todosijevic; Joseph Sarkis. Digitalizing the Closing-of-the-Loop for Supply Chains: A Transportation and Blockchain Perspective. Sustainability 2021, 13, 2895 .
AMA StyleAbdelghani Bekrar, Abdessamad Ait El Cadi, Raca Todosijevic, Joseph Sarkis. Digitalizing the Closing-of-the-Loop for Supply Chains: A Transportation and Blockchain Perspective. Sustainability. 2021; 13 (5):2895.
Chicago/Turabian StyleAbdelghani Bekrar; Abdessamad Ait El Cadi; Raca Todosijevic; Joseph Sarkis. 2021. "Digitalizing the Closing-of-the-Loop for Supply Chains: A Transportation and Blockchain Perspective." Sustainability 13, no. 5: 2895.
This paper examines a new model for hub location known as the hub location routing problem. The problem shares similarities with the well studied uncapacitated single allocation p-hub median problem except that the hubs are now connected to each other by a cyclical path (or tour) known as the global route, each cluster of non-hub nodes and assigned hub is also connected by a single tour known as a local route, and the length of the local routes is constrained to a maximum number of nodes. Thus, aside from the normal tasks of hub selection and allocation of non-hub nodes, up to p + 1 travelling salesman problems need to be solved. A heuristic based on the general variable neighborhood search framework is proposed here to solve this very complicated problem. The improvement phase of the algorithm uses a sequential variable neighborhood descent with multiple neighborhoods required to suit the complex nature of the problem. A best sequencing of the neighborhoods is established through empirical testing. The perturbation phase known as the shaking procedure also uses a well-structured selection of neighborhoods in order to effectively diversify the search to different regions of the solution space. Extensive computational testing shows that the new heuristic significantly outperforms the state-of-the-art. Out of 912 test instances from the literature, we are able to obtain 691 new best known solutions. Not only are the improvements in objective values quite impressive, but also these new solutions are obtained in a small fraction of the time required by the competing algorithms.
Mustapha Ratli; Dragan Urošević; Abdessamad Ait El Cadi; Jack Brimberg; Nenad MladenoviĆ; Raca Todosijević. An efficient heuristic for a hub location routing problem. Optimization Letters 2020, 1 -20.
AMA StyleMustapha Ratli, Dragan Urošević, Abdessamad Ait El Cadi, Jack Brimberg, Nenad MladenoviĆ, Raca Todosijević. An efficient heuristic for a hub location routing problem. Optimization Letters. 2020; ():1-20.
Chicago/Turabian StyleMustapha Ratli; Dragan Urošević; Abdessamad Ait El Cadi; Jack Brimberg; Nenad MladenoviĆ; Raca Todosijević. 2020. "An efficient heuristic for a hub location routing problem." Optimization Letters , no. : 1-20.
Scatter Search is an evolutionary metaheuristic introduced by Glover (1977) as a heuristic for integer programming and was joined with a directional rounding strategy for 0–1 Mixed Integer Programming (MIP) problems based on Star Paths in Glover (1995). In this paper, we address directional rounding both independently and together with these other algorithmic components, studying its properties as a mapping from continuous to discrete (binary) space. We establish several useful properties of directional rounding and show that it provides an extension of classical rounding and complementing operators. Moreover, we observe that directional rounding of a line, as embodied in a Star Path, contains a finite number of distinct 0–1 points. This property, together with those of the solution space of 0–1 MIP, enables us to organize the search for an optimal solution of 0–1 MIP problems using Scatter Search in association with both cutting plane and extreme point solution approaches. Building on this, we provide a Convergent Scatter Search algorithm for 0–1 Mixed Integer Programs with proof of its finite convergence, along with two variants of its implementation and examples that illustrate the running of the approach.
Raca Todosijević; Saïd Hanafi; Fred Glover. On convergence of scatter search and star paths with directional rounding for 0–1 mixed integer programs. Discrete Applied Mathematics 2020, 1 .
AMA StyleRaca Todosijević, Saïd Hanafi, Fred Glover. On convergence of scatter search and star paths with directional rounding for 0–1 mixed integer programs. Discrete Applied Mathematics. 2020; ():1.
Chicago/Turabian StyleRaca Todosijević; Saïd Hanafi; Fred Glover. 2020. "On convergence of scatter search and star paths with directional rounding for 0–1 mixed integer programs." Discrete Applied Mathematics , no. : 1.
In this paper, we propose the uncapacitated r‐allocation p‐hub center problem (UrApHCP), which represents a generalization of both single and multiple allocation variants of the p‐hub center problem. We further present two binary ‐integer linear programs for the UrApHCP and prove their equivalence for and p with respective single and multiple allocation cases. A flow formulation combining the features of the two previous models is also presented. In order to solve the UrApHCP, we develop two general variable neighborhood search (GVNS) heuristics that use nested and sequential variable neighborhood descent strategies. The proposed approaches are tested on benchmark instances from the literature with up to 423 nodes. The proposed GVNS quickly reaches all optimal or best‐known results from the literature for the single and multiple allocation variants of the problem, as well as new optimal results for r‐allocation obtained using a CPLEX solver.
Jack Brimberg; Stefan Mišković; Raca Todosijević; Dragan Uroševic. The uncapacitated r ‐allocation p ‐hub center problem. International Transactions in Operational Research 2020, 1 .
AMA StyleJack Brimberg, Stefan Mišković, Raca Todosijević, Dragan Uroševic. The uncapacitated r ‐allocation p ‐hub center problem. International Transactions in Operational Research. 2020; ():1.
Chicago/Turabian StyleJack Brimberg; Stefan Mišković; Raca Todosijević; Dragan Uroševic. 2020. "The uncapacitated r ‐allocation p ‐hub center problem." International Transactions in Operational Research , no. : 1.
In this work, we are interested in the multi-quays berth allocation and crane assignment problem under availability restrictions. Availability restrictions may arise due weather conditions, or when, for example, cranes must undergo planned maintenance in order to stay in good performance. This problem was inspired by a real-case of a bulk port in Morocco. To solve the problem we propose at first a mixed-integer programming model. Then, in view of the limitations of the proposed model, we investigate a set of heuristics based on general variable neighborhood search with three variants of variable neighborhood descent as a local search. To validate the proposed model and the proposed heuristic approach, real-world instances are used. The computational results reveal that CPLEX MIP solver consumes a lot of CPU time to solve this model, even sometimes failing to guarantee the optimality of the provided solution. On the other hand, the proposed GVNS heuristic turns out to be very efficient in solving the considered problem.
Issam Krimi; Raca Todosijević; Rachid Benmansour; Mustapha Ratli; Abdessamad Ait El Cadi; Afaf Aloullal. Modelling and solving the multi-quays berth allocation and crane assignment problem with availability constraints. Journal of Global Optimization 2020, 78, 349 -373.
AMA StyleIssam Krimi, Raca Todosijević, Rachid Benmansour, Mustapha Ratli, Abdessamad Ait El Cadi, Afaf Aloullal. Modelling and solving the multi-quays berth allocation and crane assignment problem with availability constraints. Journal of Global Optimization. 2020; 78 (2):349-373.
Chicago/Turabian StyleIssam Krimi; Raca Todosijević; Rachid Benmansour; Mustapha Ratli; Abdessamad Ait El Cadi; Afaf Aloullal. 2020. "Modelling and solving the multi-quays berth allocation and crane assignment problem with availability constraints." Journal of Global Optimization 78, no. 2: 349-373.
In this paper, we study the capacitated modular hub location problem. The problem belongs to the class of the single assignment hub location problems, where a terminal can be assigned to only one hub. In addition, the problem imposes capacity constraints, on both hubs and edges that connect them. The observed problem is directly related to the real problem. Namely, in air traffic, the number of flights between two cities directly determines the conditions of the capacity. In order to tackle the problem we propose a general variable neighborhood search (GVNS) based heuristic. We have performed exhaustive testing that led to the conclusion that the GVNS method gave superior results in comparison to the previous methods. This is especially reflected in the number of best solutions that were obtained in a much shorter time. Additionally, we applied statistical tests which showed that GVNS is undoubtedly superior with respect to the previously observed methods.
Marija Mikić; Raca Todosijević; Dragan Urošević. Less is more: General variable neighborhood search for the capacitated modular hub location problem. Computers & Operations Research 2019, 110, 101 -115.
AMA StyleMarija Mikić, Raca Todosijević, Dragan Urošević. Less is more: General variable neighborhood search for the capacitated modular hub location problem. Computers & Operations Research. 2019; 110 ():101-115.
Chicago/Turabian StyleMarija Mikić; Raca Todosijević; Dragan Urošević. 2019. "Less is more: General variable neighborhood search for the capacitated modular hub location problem." Computers & Operations Research 110, no. : 101-115.
The Cross-Docking Assignment Problem (CDAP) is a challenging optimization problem in supply chain management with important practical applications in the trucking industry. The goal is to assign incoming trucks (outgoing trucks) to inbound (outbound) doors to minimize the material handling cost within a cross-docking platform while respecting the capacity and assignment constraints. A capacity constraint is imposed on each inbound/outbound door and an associated assignment constraint is imposed on each incoming/outgoing truck requiring it to be assigned to only one inbound/outbound door. To solve this NP-hard optimization problem, we develop two novel heuristics based on Probabilistic Tabu Search utilizing a new neighborhood structure applicable both to CDAP and related problems. The proposed heuristics are evaluated on 99 benchmark instances from the literature, disclosing that our approaches outperform recent state-of-the-art approaches by reaching 45 previous best-known solutions and discovering 53 new best-known solutions while consuming significantly less CPU time.
Oualid Guemri; Placide Nduwayo; Raca Todosijević; Saïd Hanafi; Fred Glover. Probabilistic Tabu Search for the Cross-Docking Assignment Problem. European Journal of Operational Research 2019, 277, 875 -885.
AMA StyleOualid Guemri, Placide Nduwayo, Raca Todosijević, Saïd Hanafi, Fred Glover. Probabilistic Tabu Search for the Cross-Docking Assignment Problem. European Journal of Operational Research. 2019; 277 (3):875-885.
Chicago/Turabian StyleOualid Guemri; Placide Nduwayo; Raca Todosijević; Saïd Hanafi; Fred Glover. 2019. "Probabilistic Tabu Search for the Cross-Docking Assignment Problem." European Journal of Operational Research 277, no. 3: 875-885.
The goal of the less is more approach (LIMA) for solving optimization problems that has recently been proposed in Mladenović et al. (2016) is to find the minimum number of search ingredients that make a heuristic more efficient than the currently best. In this paper, LIMA is successfully applied to solve the obnoxious p‐median problem (OpMP). More precisely, we developed a basic variable neighborhood search for solving the OpMP, where the single search ingredient, the interchange neighborhood structure, is used. We also propose a new simple local search strategy for solving facility location problems, within the interchange neighborhood structure, which is in between the usual ones: first improvement and best improvement strategies. We call it facility best improvement local search. On the basis of experiments, it appeared to be more efficient and effective than both first and best improvement. According to the results obtained on the benchmark instances, our heuristic turns out to be highly competitive with the existing ones, establishing new state‐of‐the‐art results. For example, four new best‐known solutions and 133 ties are claimed in testing the set with 144 instances.
Nenad MladenoviĆ; Abdulaziz Alkandari; Jun Pei; Raca Todosijević; Panos M. Pardalos. Less is more approach: basic variable neighborhood search for the obnoxiousp-median problem. International Transactions in Operational Research 2019, 27, 480 -493.
AMA StyleNenad MladenoviĆ, Abdulaziz Alkandari, Jun Pei, Raca Todosijević, Panos M. Pardalos. Less is more approach: basic variable neighborhood search for the obnoxiousp-median problem. International Transactions in Operational Research. 2019; 27 (1):480-493.
Chicago/Turabian StyleNenad MladenoviĆ; Abdulaziz Alkandari; Jun Pei; Raca Todosijević; Panos M. Pardalos. 2019. "Less is more approach: basic variable neighborhood search for the obnoxiousp-median problem." International Transactions in Operational Research 27, no. 1: 480-493.
Hub location problems generally assume that the triangle inequality applies on the edges of a complete graph. Hence the flow between any pair of nodes requires at most two hubs for the transfer process. Here we relax the triangle inequality restriction and present two new formulations of the uncapacitated multiple allocation p-hub median problem that allow transfer through more than two hubs. Some testing is performed on newly generated instances where the triangle inequality does not hold in order to assess the tractability of these new mathematical models, and their usefulness compared to the standard approach.
Jack Brimberg; Nenad MladenoviĆ; Raca Todosijević; Dragan Urošević. A non-triangular hub location problem. Optimization Letters 2019, 14, 1107 -1126.
AMA StyleJack Brimberg, Nenad MladenoviĆ, Raca Todosijević, Dragan Urošević. A non-triangular hub location problem. Optimization Letters. 2019; 14 (5):1107-1126.
Chicago/Turabian StyleJack Brimberg; Nenad MladenoviĆ; Raca Todosijević; Dragan Urošević. 2019. "A non-triangular hub location problem." Optimization Letters 14, no. 5: 1107-1126.
A cross docking facility is a type of warehouse in supply chain management that allows orders to be prepared with or without going through the phase of storing products in the warehouse and subsequently selecting them for delivery. The goods are unloaded from incoming trucks called origins on inbound doors of a cross-docking facility platform and, using a handling device inside the platform such as a forklift, immediately transferred to outbound doors to be loaded into outgoing trucks named destinations or delivery trucks for distribution to customers. Contrary to a traditional warehouse, goods are unloaded and loaded without placing them in temporary storage inside the cross-docking facility. The goal of the cross-docking assignment problem (CDAP) is to assign origins to inbound doors and destinations to outbound doors so that the total cost inside the cross-dock platform is minimized. To the best of our knowledge, there are only three mixed integer programming (MIP) formulations of the CDAP in the literature. We propose eight new MIP models and demonstrate the mathematical equivalence of all 11 models, together with rigorously proving some of their properties. In order to detect which of these 11 models is best, we conduct an extensive comparative analysis on benchmark instances from the literature, which discloses that the best model is one proposed in this paper for the first time.
Shahin Gelareh; Fred Glover; Oualid Guemri; Saïd Hanafi; Placide Nduwayo; Raca Todosijević. A comparative study of formulations for a cross-dock door assignment problem. Omega 2018, 91, 102015 .
AMA StyleShahin Gelareh, Fred Glover, Oualid Guemri, Saïd Hanafi, Placide Nduwayo, Raca Todosijević. A comparative study of formulations for a cross-dock door assignment problem. Omega. 2018; 91 ():102015.
Chicago/Turabian StyleShahin Gelareh; Fred Glover; Oualid Guemri; Saïd Hanafi; Placide Nduwayo; Raca Todosijević. 2018. "A comparative study of formulations for a cross-dock door assignment problem." Omega 91, no. : 102015.
Local search heuristic that explores several neighborhood structures in a deterministic way is called variable neighborhood descent (VND). Its success is based on the simple fact that different neighborhood structures do not usually have the same local minimum. Thus, the local optima trap problem may be resolved by deterministic change of neighborhoods. VND may be seen as a local search routine and therefore could be used within other metaheuristics. In this chapter, we discuss typical problems that arise in developing VND heuristic: what neighborhood structures could be used, what would be their order, what rule of their change during the search would be used, etc. Comparative analysis of usual sequential VND variants is performed in solving traveling salesman problem.
Abraham Duarte; Jesús Sánchez-Oro; Nenad Mladenović; Raca Todosijević. Variable Neighborhood Descent. Handbook of Heuristics 2018, 341 -367.
AMA StyleAbraham Duarte, Jesús Sánchez-Oro, Nenad Mladenović, Raca Todosijević. Variable Neighborhood Descent. Handbook of Heuristics. 2018; ():341-367.
Chicago/Turabian StyleAbraham Duarte; Jesús Sánchez-Oro; Nenad Mladenović; Raca Todosijević. 2018. "Variable Neighborhood Descent." Handbook of Heuristics , no. : 341-367.
We present new matheuristics for the multicommodity capacitated fixed-charge network design problem (MCND). The matheuristics are based on combining iterative linear programming (ILP) methods and slope scaling (SS) heuristics. Each iteration alternates between solving a linear program obtained by adding pseudo-cuts and a restricted mixed-integer programming (MIP) model. The SS heuristic is used as a warm start to a state-of-the-art generic method that solves the restricted MIP model. The resulting ILP/SS matheuristics are compared against state-of-the-art heuristics for the MCND on a set of large-scale difficult instances. The computational results show that the approach is competitive: when performed for a time limit of 1 hour, it finds more best solutions than any other heuristic, using comparable running times; when performed for a time limit of 5 hours, it identifies an optimal solution for each instance for which an optimal solution is known and it is able to find new best solutions for some very hard instances.
Bernard Gendron; Saïd Hanafi; Raca Todosijević. Matheuristics based on iterative linear programming and slope scaling for multicommodity capacitated fixed charge network design. European Journal of Operational Research 2018, 268, 70 -81.
AMA StyleBernard Gendron, Saïd Hanafi, Raca Todosijević. Matheuristics based on iterative linear programming and slope scaling for multicommodity capacitated fixed charge network design. European Journal of Operational Research. 2018; 268 (1):70-81.
Chicago/Turabian StyleBernard Gendron; Saïd Hanafi; Raca Todosijević. 2018. "Matheuristics based on iterative linear programming and slope scaling for multicommodity capacitated fixed charge network design." European Journal of Operational Research 268, no. 1: 70-81.
The capacitated clustering problem requires finding a partition of a given set of elements with associated positive weights into a specified number of groups (or clusters) so that the sum of diversities of the individual clusters is maximized and the sum of weights of the elements in each cluster is within some capacity limits. We examine here various neighborhood structures for conducting local search for this type of problem and then describe a powerful variable neighborhood descent (VND) that employs three of these neighborhoods in a deterministic fashion and has appeared recently in the literature as a stand-alone heuristic. We then examine some recently developed heuristics for solving the problem that are based on variable neighborhood search (VNS), including a new one that applies a recently proposed variant of VNS known as nested VNS. These heuristics all use the prescribed VND in their local improvement step. A summary is given of extensive computational tests that demonstrate the effectiveness of these VNS-based heuristics over the state of the art.
Jack Brimberg; Nenad Mladenović; Raca Todosijević; Dragan Urošević. Local and Variable Neighborhood Searches for Solving the Capacitated Clustering Problem. Dynamics of Disasters 2017, 33 -55.
AMA StyleJack Brimberg, Nenad Mladenović, Raca Todosijević, Dragan Urošević. Local and Variable Neighborhood Searches for Solving the Capacitated Clustering Problem. Dynamics of Disasters. 2017; ():33-55.
Chicago/Turabian StyleJack Brimberg; Nenad Mladenović; Raca Todosijević; Dragan Urošević. 2017. "Local and Variable Neighborhood Searches for Solving the Capacitated Clustering Problem." Dynamics of Disasters , no. : 33-55.
Variable neighborhood search (VNS) is a proven heuristic framework for finding good solutions to combinatorial and global optimization problems. In this paper two VNS-based heuristics are proposed for solving the capacitated clustering problem. The first follows a standard VNS approach, and the second a skewed VNS that allows moves to inferior solutions. The performance of the two heuristics is assessed on benchmark instances from the literature. We also compare their performance against a recently published iterated VNS procedure. All VNS procedures outperform the state-of-the-art, but the Skewed VNS is best overall. This would suggest that using acceptance criteria before allowing moves to inferior solutions in Skewed VNS is preferable to the random shaking approach that is used in Iterated VNS to move to new regions of the solution space.
Jack Brimberg; Nenad Mladenovic; Raca Todosijević; Dragan Urošević. Solving the capacitated clustering problem with variable neighborhood search. Annals of Operations Research 2017, 272, 289 -321.
AMA StyleJack Brimberg, Nenad Mladenovic, Raca Todosijević, Dragan Urošević. Solving the capacitated clustering problem with variable neighborhood search. Annals of Operations Research. 2017; 272 (1-2):289-321.
Chicago/Turabian StyleJack Brimberg; Nenad Mladenovic; Raca Todosijević; Dragan Urošević. 2017. "Solving the capacitated clustering problem with variable neighborhood search." Annals of Operations Research 272, no. 1-2: 289-321.
Zhazira Amirgaliyeva; Nenad Mladenovic; Raca Todosijević; Dragan Urošević. Solving the maximum min-sum dispersion by alternating formulations of two different problems. European Journal of Operational Research 2017, 260, 444 -459.
AMA StyleZhazira Amirgaliyeva, Nenad Mladenovic, Raca Todosijević, Dragan Urošević. Solving the maximum min-sum dispersion by alternating formulations of two different problems. European Journal of Operational Research. 2017; 260 (2):444-459.
Chicago/Turabian StyleZhazira Amirgaliyeva; Nenad Mladenovic; Raca Todosijević; Dragan Urošević. 2017. "Solving the maximum min-sum dispersion by alternating formulations of two different problems." European Journal of Operational Research 260, no. 2: 444-459.
This paper deals with uncapacitated single and multiple allocation p-hub maximal covering problems (USApHMCP and UMApHMCP) with binary and partial covering criteria. We present new mixed-integer programming formulations of the considered problems, which are valid for both binary and partial coverage cases. The efficiency of the proposed formulations is evaluated through computational experiments on smaller-size instances, and compared with the state-of-the art models from the literature. The obtained results indicate that the new UMApHMCP formulation outperforms the existing one for both coverage criteria in the sense of solutions’ quality and running times. In order to solve instances of larger problem dimension, we develop two heuristic methods based on variable neighborhood search: general VNS (GVNS) for USApHMCP and basic VNS (BVNS) for UMApHMCP. The proposed GVNS and BVNS involve the same shaking procedure in order to hopefully escape local minima traps, while local search phases in GVNS and BVNS use different neighborhood structures in accordance with applied allocation schemes. Computational experiments conducted on smaller-size instances showed that both GVNS and BVNS almost instantly reach all known optimal solutions. In addition, the proposed GVNS and BVNS showed to be very efficient when solving large and large-scale hub instances with up to 1000 nodes, which were not previously considered as test instances for the considered problems. Both GVNS and BVNS provided best solutions on challenging USApHMCP and UMApHMCP instances for both coverage cases in short running times, which indicates their potential to be applied to similar problems.
Olivera Janković; Stefan Mišković; Zorica Stanimirović; Raca Todosijević. Novel formulations and VNS-based heuristics for single and multiple allocation p-hub maximal covering problems. Annals of Operations Research 2017, 259, 191 -216.
AMA StyleOlivera Janković, Stefan Mišković, Zorica Stanimirović, Raca Todosijević. Novel formulations and VNS-based heuristics for single and multiple allocation p-hub maximal covering problems. Annals of Operations Research. 2017; 259 (1-2):191-216.
Chicago/Turabian StyleOlivera Janković; Stefan Mišković; Zorica Stanimirović; Raca Todosijević. 2017. "Novel formulations and VNS-based heuristics for single and multiple allocation p-hub maximal covering problems." Annals of Operations Research 259, no. 1-2: 191-216.
Jack Brimberg; Nenad MladenoviĆ; Raca Todosijević; Dragan Urošević. A general framework for nested variable neighborhood search. Electronic Notes in Discrete Mathematics 2017, 58, 159 -166.
AMA StyleJack Brimberg, Nenad MladenoviĆ, Raca Todosijević, Dragan Urošević. A general framework for nested variable neighborhood search. Electronic Notes in Discrete Mathematics. 2017; 58 ():159-166.
Chicago/Turabian StyleJack Brimberg; Nenad MladenoviĆ; Raca Todosijević; Dragan Urošević. 2017. "A general framework for nested variable neighborhood search." Electronic Notes in Discrete Mathematics 58, no. : 159-166.
Jack Brimberg; Nenad Mladenovic; Raca Todosijević; Dragan Urošević. Less is more: Solving the Max-Mean diversity problem with variable neighborhood search. Information Sciences 2017, 382-383, 179 -200.
AMA StyleJack Brimberg, Nenad Mladenovic, Raca Todosijević, Dragan Urošević. Less is more: Solving the Max-Mean diversity problem with variable neighborhood search. Information Sciences. 2017; 382-383 ():179-200.
Chicago/Turabian StyleJack Brimberg; Nenad Mladenovic; Raca Todosijević; Dragan Urošević. 2017. "Less is more: Solving the Max-Mean diversity problem with variable neighborhood search." Information Sciences 382-383, no. : 179-200.
Local search heuristic that explores several neighborhood structures in a deterministic way is called variable neighborhood descent (VND). Its success is based on the simple fact that different neighborhood structures do not usually have the same local minimum. Thus, the local optima trap problem may be resolved by deterministic change of neighborhoods. VND may be seen as a local search routine and therefore could be used within other metaheuristics. In this chapter, we discuss typical problems that arise in developing VND heuristic: what neighborhood structures could be used, what would be their order, what rule of their change during the search would be used, etc. Comparative analysis of usual sequential VND variants is performed in solving traveling salesman problem.
Abraham Duarte; Nenad MladenoviĆ; Jesús Sánchez-Oro; Raca Todosijević. Variable Neighborhood Descent. Handbook of Heuristics 2016, 1 -27.
AMA StyleAbraham Duarte, Nenad MladenoviĆ, Jesús Sánchez-Oro, Raca Todosijević. Variable Neighborhood Descent. Handbook of Heuristics. 2016; ():1-27.
Chicago/Turabian StyleAbraham Duarte; Nenad MladenoviĆ; Jesús Sánchez-Oro; Raca Todosijević. 2016. "Variable Neighborhood Descent." Handbook of Heuristics , no. : 1-27.
Variable neighborhood search (VNS) is a framework for building heuristics, based upon systematic changes of neighborhoods both in a descent phase, to find a local minimum, and in a perturbation phase to escape from the corresponding valley. In this paper, we present some of VNS basic schemes as well as several VNS variants deduced from these basic schemes. In addition, the paper includes parallel implementations and hybrids with other metaheuristics.
Pierre Hansen; Nenad Mladenović; Raca Todosijević; Saïd Hanafi. Variable neighborhood search: basics and variants. EURO Journal on Computational Optimization 2016, 5, 423 -454.
AMA StylePierre Hansen, Nenad Mladenović, Raca Todosijević, Saïd Hanafi. Variable neighborhood search: basics and variants. EURO Journal on Computational Optimization. 2016; 5 (3):423-454.
Chicago/Turabian StylePierre Hansen; Nenad Mladenović; Raca Todosijević; Saïd Hanafi. 2016. "Variable neighborhood search: basics and variants." EURO Journal on Computational Optimization 5, no. 3: 423-454.