Bu çalışmada Çoklu Şarj Teknolojisine Dayalı Kısmi Şarj Politikalı Karma Filolu Elektrikli Araç Rotalama Problemi (KF-E-ARP) ele alınmıştır. Karma filo, elektrikli araçları (EA) ve konvansiyonel ...araçları (KA) içermektedir. Konvansiyonel araçların emisyon fonksiyonu ve elektrikli araçların şarj tüketim fonksiyonu içerisinde katedilen mesafe ile birlikte araçta taşınan yük miktarı da dikkate alınmıştır. Ayrıca şarj istasyonunda çoklu şarj konfigürasyonlarından birinin seçilmesi, karma filolu problemlerde ilk defa ele alınmıştır. Problem, müşteri dağıtım taleplerini karşılarken toplam maiyeti enazlayan araç rotalarının elde edilmesi olarak tanımlanabilir. KF-E-ARP için öncelikle karma tamsayılı matematiksel model geliştirilmiştir. Problem NP-zor olduğundan dolayı, orta ve büyük boyutlu problemlere makul sürelerde çözüm elde edebilmek amacıyla ekleme tabanlı bir çözüm kurucu sezgisel algoritma önerilmiştir. Deneysel analizlerde, matematiksel model ile 2 saat içerisinde çözüm bulunamayan tüm orta ve büyük boyutlu problemlere önerilen çözüm kurucu sezgisel algoritmalar ile yaklaşık 1 saniye gibi çok kısada sürede uygun çözümler bulunabildiğini gözlemlenmiştir.
This paper introduces, models, and solves a rich vehicle routing problem (VRP) motivated by the case study of replenishment of automated teller machines (ATMs) in Turkey. In this practical problem, ...commodities can be taken from the depot, as well as from the branches to efficiently manage the inventory shortages at ATMs. This rich VRP variant concerns with the joint multiple depots, pickup and delivery, multi-trip, and homogeneous fixed vehicle fleet. We first mathematically formulate the problem as a mixed-integer linear programming model. We then apply a Geographic Information System (GIS)-based solution method, which uses a tabu search heuristic optimization method, to a real dataset of one of the major bank. Our numerical results show that we are able to obtain solutions within reasonable solution time for this new and challenging practical problem. The paper presents computational and managerial results by analyzing the trade-offs between various constraints.
•We present a comprehensive and up-to-date review of the Vehicle Routing Problem with Backhauls (VRPB).•We provide a comparative analysis of the performance of the state-of-the-art heuristics for the ...standard VRPB.•We describe several extensions of the VRPB, as well as a number of industrial applications and case studies.•We provide some future research directions.
In the Vehicle Routing Problem with Backhauls (VRPB), the customer set is partitioned into linehaul customers who require deliveries, and backhaul customers who require pickups. Both the linehaul customers and the backhaul customers must be visited contiguously, and all routes must contain at least one linehaul customer. All deliveries have to be loaded at the depot, and all pickups up have to be transported to the depot. This survey paper aims to comprehensively review the existing literature on VRPBs, including models, exact and heuristic algorithms, variants, industrial applications and case studies, with an emphasis on the recent literature. The paper contains several synthetic tables and proposes a number of promising research directions.
Thirty years of heterogeneous vehicle routing Koç, Çağrı; Bektaş, Tolga; Jabali, Ola ...
European journal of operational research,
02/2016, Letnik:
249, Številka:
1
Journal Article
Recenzirano
Odprti dostop
•The paper classifies heterogeneous vehicle routing problems (HVRPs).•A comprehensive and up-to-date review of the existing work on HVRPs is presented.•A comparative analysis of the metaheuristics ...proposed for HVRPs is provided.
It has been around 30 years since the heterogeneous vehicle routing problem was introduced, and significant progress has since been made on this problem and its variants. The aim of this survey paper is to classify and review the literature on heterogeneous vehicle routing problems. The paper also presents a comparative analysis of the metaheuristic algorithms that have been proposed for these problems.
•We survey the Vehicle Routing with Simultaneous Pickup and Delivery (VRPSPD).•We provide a performance comparison of heuristics developed for the VRPSPD.•We describe several problem variants, case ...studies and industrial applications.•We give an overview of the main trends observed in the literature.•We identify several interesting promising future research perspectives.
In the vehicle routing problem with simultaneous pickup and delivery (VRPSPD), goods have to be transported from different origins to different destinations, and each customer has both a delivery and a pickup demand to be satisfied simultaneously. The VRPSPD has been around for about 30 years, and significant progress has since been made on this problem and its variants. This paper aims to comprehensively review the existing work on the VRPSPD. It surveys mathematical formulations, algorithms, variants, case studies, and industrial applications. It also provides an overview of trends in the literature and identifies several interesting promising future research perspectives.
The road transportation is one of the largest contributors to greenhouse gas emissions globally, and rapid urbanisation increases the environmental and economic challenges. Electric vehicles support ...green supply chain and clean routing operations when compared with the traditional fossil fuel-powered vehicles. This paper analyses a variant of the home health care routing problem in which a group of health care workers performs a requested number of jobs by using electric vehicles. The problem considers multi-depot, heterogeneous fleet, time windows, preferences, competencies, connected activities, the range of electric vehicles, charging status, and charge strategies. We develop a hybrid metaheuristic which successfully combines genetic algorithm and a variable neighbourhood descent, and offer several algorithmic procedures tailored to handle the rich constraints of the problem. Extensive computational experiments on small, medium and large-scale instances have shown that the hybrid metaheuristic is effective on the problem.
•We develop a solution approach to solve the green vehicle routing problem.•We propose a simulated annealing heuristic to improve the quality of solutions.•We present a new formulation having fewer ...variable and constraints.•We evaluate the algorithm in terms of the several performance criterions.•Our algorithm is able to optimally solve 22 of 40 benchmark instances.
This paper develops a simulated annealing heuristic based exact solution approach to solve the green vehicle routing problem (G-VRP) which extends the classical vehicle routing problem by considering a limited driving range of vehicles in conjunction with limited refueling infrastructure. The problem particularly arises for companies and agencies that employ a fleet of alternative energy powered vehicles on transportation systems for urban areas or for goods distribution. Exact algorithm is based on the branch-and-cut algorithm which combines several valid inequalities derived from the literature to improve lower bounds and introduces a heuristic algorithm based on simulated annealing to obtain upper bounds. Solution approach is evaluated in terms of the number of test instances solved to optimality, bound quality and computation time to reach the best solution of the various test problems. Computational results show that 22 of 40 instances with 20 customers can be solved optimally within reasonable computation time.
This paper analyses the joint impact of depot location and routing decisions on emissions in freight transportation. We study a variant of the location-routing problem by considering environmental ...objectives and time windows. The aim is to minimize the sum of depot cost, driver cost, and the cost of fuel and CO
2
emissions. The paper develops an adaptive large neighborhood search metaheuristic which was applied to a large pool of benchmark instances and offers a number of advanced procedures. Extensive analyses assess the effect of various problem parameters, such as depot cost, number of potential depots and depot capacity, on key performance indicators. The paper also offers several managerial and policy insights on economies of environmental friendly location-routing.
This paper presents a hybrid evolutionary algorithm (HEA) to solve heterogeneous fleet vehicle routing problems with time windows. There are two main types of such problems, namely the fleet size and ...mix vehicle routing problem with time windows (F) and the heterogeneous fixed fleet vehicle routing problem with time windows (H), where the latter, in contrast to the former, assumes a limited availability of vehicles. The main objective is to minimize the fixed vehicle cost and the distribution cost, where the latter can be defined with respect to en-route time (T) or distance (D). The proposed unified algorithm is able to solve the four variants of heterogeneous fleet routing problem, called FT, FD, HT and HD, where the last variant is new. The HEA successfully combines several metaheuristics and offers a number of new advanced efficient procedures tailored to handle the heterogeneous fleet dimension. Extensive computational experiments on benchmark instances have shown that the HEA is highly effective on FT, FD and HT. In particular, out of the 360 instances we obtained 75 new best solutions and matched 102 within reasonable computational times. New benchmark results on HD are also presented.
•We develop a unified algorithm for four heterogeneous routing problems.•We introduce a new heterogeneous routing problem.•The algorithm combines two state-of-the-art metaheuristic concepts.•Out of the 360 instances we obtain 75 strictly new best solutions.
This paper studies the green vehicle routing problem with simultaneous pickup and delivery (G-VRPSPD). It aims to minimize fuel consumption costs while satisfying customer pickup and delivery demands ...simultaneously. The fuel consumption is directly proportional to green house gas emissions. We mathematically formulate the problem, and develop a hyper-heuristic (HH-ILS) algorithm based on iterative local search and variable neighborhood descent heuristics to effectively solve the problem. Extensive computational experiments are conducted to analyze the impact of the G-VRPSPD and the HH-ILS. We investigate the effect of green objective function on total fuel consumption cost by comparing the G-VRPSPD with the VRPSPD. We perform comparative analysis to investigate the performance of HH-ILS. We also conduct sensitivity analysis to investigate the performance of neighborhood structures, hyper heuristic and local search. The results show that the green objective function has a significant effect on total fuel consumption cost. The HH-ILS algorithm yields competitive results when compared with the mathematical formulation and the state-of-the-art heuristics in the literature.
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