scholarly journals Lion optimization algorithm for team orienteering problem with time window

2021 ◽  
Vol 21 (1) ◽  
pp. 538
Author(s):  
Esam Taha Yassen ◽  
Alaa Abdulkhar Jihad ◽  
Sudad H. Abed
Keyword(s):  
Optimization Algorithm ◽  
Optimization Problems ◽  
Time Window ◽  
Time Windows ◽  
Real Life ◽  
Search Space ◽  
Orienteering Problem ◽  
Team Orienteering Problem ◽  
Team Orienteering ◽  
Lion Optimization Algorithm

<span>Over the last decade, many nature-inspired algorithms have been received considerable attention among practitioners and researchers to handle several optimization problems. Lion optimization algorithm (LA) is inspired by a distinctive lifestyle of lions and their collective behavior in their social groups. LA has been presented as a powerful optimization algorithm to solve various optimization problems. In this paper, the LA is proposed to investigate its performance in solving one of the most popular and widespread real-life optimization problems called team orienteering problem with time windows (TOPTW). However, as any population-based metaheuristic, the LA is very efficient in exploring the search space, but inefficient in exploiting it. So, this paper proposes enhancing LA to tackle the TOPTW by utilizing its strong ability to explore the search space and improving its exploitation ability. This enhancement is achieved via improving a process of territorial defense to generate a trespass strong nomadic lion to prevail a pride by fighting its males. As a result of this improving process, an enhanced LA (ILA) emerged. The obtained solutions have been compared with the best known and standard results obtained in the former studies. The conducted experimental test verifies the effectiveness of the ILA in solving the TOPTW as it obtained a very competitive results compared to the LA and the state-of-the-art methods across all tested instances.</span>

Efficient Cluster-Based Heuristics for the Team Orienteering Problem with Time Windows

2019 ◽  
Vol 36 (01) ◽  
pp. 1950001 ◽  
Author(s):  
Damianos Gavalas ◽  
Charalampos Konstantopoulos ◽  
Konstantinos Mastakas ◽  
Grammati Pantziou
Keyword(s):  
Execution Time ◽  
Time Window ◽  
Time Budget ◽  
Time Windows ◽  
Experimental Tests ◽  
Orienteering Problem ◽  
Solution Quality ◽  
Routing Problem ◽  
Team Orienteering Problem ◽  
Team Orienteering

In the Team Orienteering Problem with Time Windows (TOPTW), a variant of the Vehicle Routing Problem with Profits, a set of locations is given, each associated with a profit, a visiting time and a time window. The aim is to maximize the overall profit collected by a number of routes, while the duration of each route must not exceed a given time budget. TOPTW is NP-hard and is typically used to model the Tourist Trip Design Problem. The latter deals with deriving near optimal multiple-day tours for tourists visiting a destination with several points of interest (POIs). The most efficient known heuristic approach to TOPTW which yields the best solution quality versus execution time, is based on Iterated Local Search (ILS). However, the ILS algorithm treats each node separately, hence it tends to overlook highly profitable areas of nodes situated far from the current solution, considering them too time-expensive to visit. We propose two cluster-based extensions to ILS addressing the aforementioned weakness by grouping nodes on separate clusters (based on geographical criteria), thereby making visits to such nodes more attractive. Our approaches improve ILS with respect to solutions quality and execution time as evidenced by experimental tests exercised on both existing and new TTDP-oriented benchmark instances.

A multi-objective evolutionary hyper-heuristic algorithm for team-orienteering problem with time windows regarding rescue applications

2019 ◽  
Vol 34 ◽  
Author(s):  
Hadi S. Aghdasi ◽  
Saeed Saeedvand ◽  
Jacky Baltes
Keyword(s):  
Heuristic Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Humanoid Robots ◽  
Orienteering Problem ◽  
Urban Search And Rescue ◽  
Sports Teams ◽  
Multi Objective ◽  
Team Orienteering Problem ◽  
Team Orienteering

Abstract The team-orienteering problem (TOP) has broad applicability. Examples of possible uses are in factory and automation settings, robot sports teams, and urban search and rescue applications. We chose the rescue domain as a guiding example throughout this paper. Hence, this paper explores a practical variant of TOP with time window (TOPTW) for rescue applications by humanoid robots called TOPTWR. Due to the significant range of algorithm choices and their parameters tuning challenges, the use of hyper-heuristics is recommended. Hyper-heuristics can select, order, or generate different low-level heuristics with different optimization algorithms. In this paper, first, a general multi-objective (MO) solution is defined, with five objectives for TOPTWR. Then a robust and efficient MO and evolutionary hyper-heuristic algorithm for TOPTW based on the humanoid robot’s characteristics in the rescue applications (MOHH-TOPTWR) is proposed. MOHH-TOPTWR includes two MO evolutionary metaheuristics algorithms (MOEAs) known as non-dominated sorting genetic algorithm (NSGA-III) and MOEA based on decomposition (MOEA/D). In this paper, new benchmark instances are proposed for rescue applications using the existing ones for TOPTW. The experimental results show that MOHH-TOPTWR in both MOEAs can outperform all the state-of-the-art algorithms as well as NSGA-III and MOEA/D MOEAs.

scholarly journals Uncertain Team Orienteering Problem With Time Windows Based on Uncertainty Theory

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 63403-63414 ◽  
Author(s):  
Jian Wang ◽  
Jiansheng Guo ◽  
Jicheng Chen ◽  
Shan Tian ◽  
Taoyong Gu
Keyword(s):  
Uncertainty Theory ◽  
Time Windows ◽  
Orienteering Problem ◽  
Team Orienteering Problem ◽  
Team Orienteering

scholarly journals New Formulations for the Team Orienteering Problem

2016 ◽  
Vol 6 (2) ◽  
pp. 70-77
Author(s):  
Tusan Derya ◽  
Imdat Kara ◽  
Papatya Sevgin Bicakci ◽  
Baris Kececi
Keyword(s):  
Traveling Salesman Problem ◽  
Real Life ◽  
Traveling Salesman ◽  
Orienteering Problem ◽  
Routing Problems ◽  
Practical Applications ◽  
Team Orienteering Problem ◽  
Benchmark Instances ◽  
Team Orienteering ◽  
Predetermined Time

Routing problems have many practical applications in distribution and logistics management. The Traveling Salesman Problem (TSP) and its variants lie at the heart of routing problems. The Orienteering Problem (OP) is a subset selection version of well-known TSP which comes from an outdoor sport played on mountains. In the OP, the traveller must finish its journey within a predetermined time (cost, distance), and gets a gain (profit, reward) from the visited nodes. The objective is to maximize the total gain that the traveller collects during the predetermined time. The OP is also named as the selective TSP since not all cities have to be visited. The Team Orienteering Problem (TOP) is the extension of OP by multiple-traveller. As far as we know, there exist a few formulations for the TOP. In this paper we present two new integer linear programming formulations (ILPFs) for the TOP with O(n2) binary variables and O(n2) constraints, where n is the number of nodes on the underlying graph. The proposed formulations can be directly used for the OP when we take the number of traveller as one. We demonstrate that, additional restrictions and/or side conditions can be easily imported for both of the formulations. The performance of our formulations is tested on the benchmark instances from the literature. The benchmark instances are solved via CPLEX 12.6 by using the proposed and existing formulations. The computational experiments demonstrate that both of the new formulations outperform the existing one. The new formulations are capable of solving optimally most of the benchmark instances, which have solved by using special heuristics so far. As a result, the proposed formulations can be used to find the optimal solution of small- and moderate-size real life OP and TOP by using an optimizer.   Keywords: Traveling salesman problem, orienteering problem, modeling;

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