scholarly journals Exact and heuristic solution approaches for the Integrated Job Scheduling and Constrained Network Routing Problem

2014 ◽  
Vol 164 ◽  
pp. 121-137 ◽  
Author(s):  
Mette Gamst
Author(s):  
Juan Carlos Rivera ◽  
Victoria J. Zapata

Welfare community projects, mainly related to health care, are essential for the development of societies. For this reason, the optimization of its resources through methodologies that support decision making becomes of interest for all stakeholders in order to reach the target users. In Colombia, particularly in the city of Medellin, several social projects are being developed seeking to provide health and other social services to vulnerable populations. The purpose of this chapter is to deal with a real application of the home health care routing and scheduling problem (HHCRSP), in which a set of health professionals grouped by teams should visit a set of users geographically scatter over the city. Here, it is proposed a mixed integer linear model and a heuristic solution approach. The mathematical model is based on vehicle routing problem with pickups and deliveries (VRPPD) with additional features related with the specific application and geographical conditions.


2020 ◽  
Vol 10 (7) ◽  
pp. 2403
Author(s):  
Yanjun Shi ◽  
Lingling Lv ◽  
Fanyi Hu ◽  
Qiaomei Han

This paper addresses waste collection problems in which urban household and solid waste are brought from waste collection points to waste disposal plants. The collection of waste from the collection points herein is modeled as a multi-depot vehicle routing problem (MDVRP), aiming at minimizing the total transportation distance. In this study, we propose a heuristic solution method to address this problem. In this method, we firstly assign waste collection points to waste disposal plants according to the nearest distance, then each plant solves the single-vehicle routing problem (VRP) respectively, assigning customers to vehicles and planning the order in which customers are visited by vehicles. In the latter step, we propose the sector combination optimization (SCO) algorithm to generate multiple initial solutions, and then these initial solutions are improved using the merge-head and drop-tail (MHDT) strategy. After a certain number of iterations, the optimal solution in the last generation is reported. Computational experiments on benchmark instances showed that the initial solutions obtained by the sector combination optimization algorithm were more abundant and better than other iterative algorithms using only one solution for initialization, and the solutions with distance gap were obtained using the merge-head and drop-tail strategy in a lower CPU time compared to the Tabu search algorithm.


2016 ◽  
Vol 17 (3) ◽  
pp. 1-9 ◽  
Author(s):  
Ameen Oloduowo ◽  
Akande Babalola ◽  
Aruleba Daniel

2021 ◽  
Author(s):  
Ali Mahmoodirad ◽  
Behzad Aghaei Fishani ◽  
Sadegh Niroomand ◽  
Mohammad Fallah

Abstract In this study a multi-objective formulation is proposed for designing a supply chain of perishable products including suppliers, plants, distributors, and customers under sustainable development. In addition to the studies of the literature, direct shipment between producers and customers and also alternative products possibility are allowed. In this problem the objectives like facilities establishment costs, transportation costs, negative environmental impacts, and social impact (fixed and variable employment rates) are optimized simultaneously. As in real situations, most of the transportation activities of such supply chain are performed by hiring transportation devices, the open routing logic is applied to form the travelling path of each hired transportation device. Furthermore, the possibility of direct shipment from the plants to the customers is considered in order to increase profitability of the plants. Because of the NP-hard nature of the supply chain design problems, some meta-heuristic solution approaches of the literature are modified to multi-objective form and applied to solve the problem. Several test problems from small to large sizes are generated randomly to evaluate the meta-heuristic algorithms. As a result, among the proposed algorithms, the multi-objective grey wolf optimizer (MGWO) perform better than others by considering four well-known evaluation metrics. At the end, a case study from perishable products supply chain of Iran is solved and analyzed to show the applicability of the proposed problem.


Author(s):  
Mehmet Sevkli ◽  
Abdullah S. Karaman ◽  
Yusuf Ziya Unal ◽  
Muheeb Babajide Kotun

In this chapter, a single depot, long-distance heterogeneous vehicle routing problem is studied with fixed costs and vehicle-dependent routing costs (LD-HVRPFD). The LD-HVRPFD considers retailers far away from the single depot and hence route durations could exceed a day. Thus, the number of available vehicles changes through the course of the multi-day planning horizon. Moreover, it is typical to encounter time-variant demand from retailers. To solve the LD-HVRPFD, the authors developed an iterative heuristic solution methodology integrated into a programming platform. The solution method consists of decomposing the VRP into sequential daily problems, model building using macro programming, obtaining a solution using a solver, determining the route-vehicle pairs and time durations, and dynamically updating the truck availability for the next day. The method is illustrated using real data from one of the biggest retail companies in the ready-to-wear sector of textile supply chains. The performance of the heuristic optimization procedure based on time and gap restriction criteria is presented.


2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Sungwook Kim

Mobile ad hoc network represents a system of wireless mobile nodes that can freely and dynamically self-organize network topologies without any preexisting communication infrastructure. Due to characteristics like temporary topology and absence of centralized authority, routing is one of the major issues in ad hoc networks. In this paper, a new multipath routing scheme is proposed by employing simulated annealing approach. The proposed metaheuristic approach can achieve greater and reciprocal advantages in a hostile dynamic real world network situation. Therefore, the proposed routing scheme is a powerful method for finding an effective solution into the conflict mobile ad hoc network routing problem. Simulation results indicate that the proposed paradigm adapts best to the variation of dynamic network situations. The average remaining energy, network throughput, packet loss probability, and traffic load distribution are improved by about 10%, 10%, 5%, and 10%, respectively, more than the existing schemes.


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