scholarly journals New Formulations for the Team Orienteering Problem

Author(s):  
Tusan Derya ◽  
Imdat Kara ◽  
Papatya Sevgin Bicakci ◽  
Baris Kececi

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;


Author(s):  
Esam Taha Yassen ◽  
Alaa Abdulkhar Jihad ◽  
Sudad H. Abed

<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>



Author(s):  
Christopher Bayliss ◽  
◽  
Pedro Copado-Mendez ◽  
Javier Pandero ◽  
Angel A. Juan ◽  
...  




2013 ◽  
Vol 224 (1) ◽  
pp. 65-78 ◽  
Author(s):  
C.D. Tarantilis ◽  
F. Stavropoulou ◽  
P.P. Repoussis


2021 ◽  
Author(s):  
Ariella Mansfield ◽  
Sandeep Manjanna ◽  
Douglas G. Macharet ◽  
M. Ani Hsieh


2019 ◽  
Vol 28 (1) ◽  
pp. 77-83
Author(s):  
CAMELIA-M. PINTEA ◽  
◽  
BARNA IANTOVICS ◽  
PETRICA POP ◽  
MATTHIAS DEHMER ◽  
...  

Nowadays, routing problems arise in different contexts of distribution of goods, transportation of commodities and people. Routing problems deals with traveling along a given network in an optimal way. One of the major goals in optimization, including optimization of routing problems, is to reduce the time of stagnation by finding an exit state. The current work is a study about the ability of ants to escape from solution stagnation on a particular routing problem, the Traveling Salesman Problem.



2013 ◽  
Vol 229 (3) ◽  
pp. 673-682 ◽  
Author(s):  
Zhixing Luo ◽  
Brenda Cheang ◽  
Andrew Lim ◽  
Wenbin Zhu


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