A Genetic Algorithm for a Green Vehicle Routing Problem

We propose a Genetic Algorithm (GA) to address a Green Vehicle Routing Problem (G-VRP). Unlike classic formulations of the VRP, this study aims to minimise the CO2 emissions per route. The G-VRP is of interest to policy makers who wish to reduce greenhouse gas emissions. The GA is tested on a suite of benchmark, and real-world instances which include road speed and gradient data. Our solution approach incorporates elements of local and population search heuristics. Solutions are compared with routes currently used by drivers in a courier company. Reductions in emissions are achieved without incurring additional operational costs

Genetic Algorithm Approach to Logistics Transportation and Distribution Problems: A Case Study of Parcel Delivery Services

Transportation and distribution activities require companies to have careful transportation planning to maintain resource efficiency. One form of planning in the transportation is planning the route and the number of vehicles. The research output is to get the best shipping route from each transportation in the form of the smallest shipping cost, delivery distance and shortest time. The approach used to determine the best route is the genetic algorithm (GA) method. In the application of GA in finding routes according to the objective, it gives the best results. From the results of the study, it was concluded that the GA algorithm was able to produce the best route effectiveness of 35.5% with a minimum distance of 76.4 km with the route 1-16-7-14-13-17-21-22-6-19-18 - 3-23-9-19-15-24-4-15-20-8-11-2-25-5-2 and a travel time of 4 hours 51 minutes and a fee of Rp. 213,000 with a delivery route on the test

Diseño de una técnica de solución para el problema de enrutamiento de vehículos considerando factores ambientales

The Vehicle routing problem has been widely studied in the literature due to its impact on the operative decisions of any company that needs to deliver or pick-up merchandise. The current situation of the earth has led organizations to keep in mind the environmental factor in their operations. Therefore, it has been recently introduced to this area of study the green vehicle routing problem (GVRP), which aims to minimize the total amount of fuel consumed and CO2 generated by the fleet of vehicles. This thesis proposes several solution techniques to respond to the GVRP applied on a real-life scenario of a manufacturing company in Bogotá. For this purpose, an integer programming model and three different algorithms had been developed, namely, a heuristic, a tabú and a genetic algorithm. In order to measure the quality of the solutions different instances were made with three main variants: the number of clients, the number of vehicles, and the speed. The model, the heuristic, and the tabú algorithm were evaluated with and without time windows, the genetic algorithm was only considered for scenarios without time windows. The results obtained show that the genetic algorithm achives better values of the solution than the other desing methods, hence, this algorithm was applied to the real- life scenario. The solution method was able to reduce in 21,90% the total emission generated in comparison with the current operation.Ingeniero (a) IndustrialPregrad

Heterojen Filolu Yeşil Araç Rotalama Probleminin Tavlama Benzetimi Yöntemi ile Çözümü

Araç rotalama problemi, müşterilere siparişlerini ulaştırmak için minimum maliyetli rota kümesinin belirlendiği optimizasyon problemidir. Son yıllarda çevresel duyarlılıktaki artışla beraber, uygulayıcılar ve araştırmacılar fosil yakıtların çevreye olan etkilerini azaltmak için taşıma faaliyetlerinin çevre ile ilgili özelliklerine odaklanmaya başlamıştır. Araç rotalama probleminin bu duyarlılığı dikkate alan türü ise yeşil araç rotalama problemi olarak adlandırılmaktadır. Yeşil araç rotalama problemi son yıllarda üzerinde oldukça yoğun çalışılan bir konudur. Çalışmanın ana motivasyonu, güncel hayatta doğal olarak karşılaşılan heterojen araç filoları için yük toplama/dağıtma rotalarının işlemesi sonucu ortaya çıkan emisyon gazlarının minimize edilmesi amacıyla bir yaklaşım geliştirmektir. Çalışmada, bölge distribütörü olarak faaliyet gösteren bir firmanın dağıtım faaliyetleri heterojen filolu yeşil araç rotalama problemi olarak ele alınmış ve tavlama benzetimi yöntemiyle daha düşük emisyon değerleri sağlayan çevreci çözümler elde edilmeye çalışılmıştır. Çözüm yaklaşımında heterojen bir filo için emisyon değerleri araçların taşıdığı yük miktarı ve yüklerin taşındığı mesafe üzerinden hesaplanmıştır. Yeşil Araç Rotalama çözümleri, standart araç rotalama problemi olarak elde edilen çözümler üzerinden hesaplanan emisyon değerleri ile kıyaslanmıştır. Sonuç olarak, yük miktarı, taşıma mesafesi ve emisyon salınımı ilişkileri nedeniyle önerilen yaklaşım bazı veri setlerinde daha yüksek dolaşım mesafesine karşın daha düşük emisyon miktarı içeren çözümler sağlamıştır. Bütün çözümlerin toplam değeri göz önüne alındığında, seyahat mesafesi bakımından %38,5 ve emisyon değeri bakımından ise %86,7 oranında daha iyi çözümler elde edilmiştir

Business Model Evaluation: A Systematic Review of Methods

Background: As a result of factors such as digitization and rapid technology change, organizations are compelled to innovate their business models at an accelerated pace. While the domain of business model innovation has focused on understanding and structuring the process of innovation, it offers limited guidance for evaluating business models during the innovation process. Business model evaluation plays a vital role in supporting decision-making about the performance or viability of new business models and motivating continued investments. Existing literature on methods for business model evaluation and their application is limited and available information is scattered. Furthermore, as the BMI process covers a broad spectrum of activities - from business model initiation to implementation - the evaluation challenges and the effectiveness of evaluation methods vary across the phases of innovation. Thus, there is a need for a better understanding on methods for business model evaluation, and their timing and application for business model innovation. Method: Through a systematic literature review, we have investigated the methods available for business model evaluation and focused on understanding their characteristics and effective timing of application in the business model innovation process. Results: We have identified six groups of methods used for business model evaluation. Additionally, we find that early phase business model evaluation is predominantly qualitative in nature, whereas late phases of business model innovation are generally supported through quantitatively-oriented methods. Moreover, we observe that limited evaluation support is available in the literature to support the initiation phase of business model innovation. Based on our findings, we propose a guiding structure for aligning the available methods with the respective innovation phases. Conclusion: The proposed guiding structure offers guidance for business model evaluation in practice and serves as a basis for future research in developing more effective methods and tools for business model evaluation and development

A review of recent advances in the operations research literature on the green routing problem and its variants

Since early 2010s, the Green Routing Problem (GRP) has dominated the literature of logistics and transportation. The problem itself consists of finding a set of vehicle routes for a set of customers while minimizing the detrimental effects of transportation activities. These negative externalities have been intensively tackled in the last decade. Operations research studies have particularly focused on minimizing the energy consumption and emissions. As a result, the rich literature on GRPs has already reached its peak, and several early literature reviews have been conducted on various aspects of related vehicle routing and scheduling problem variants. The major contribution of this paper is that it represents a comprehensive review of the current reviews on GRP studies. In addition to that, it is an up-to-date review based on a new chronological taxonomy of the literature. The detailed analysis provides a useful framework for understanding the research gaps for the future studies and the potential impacts for the academic community

A Genetic Algorithm for a Green Vehicle Routing Problem

International Network Optimization Conference 2017 (INOC 2017), Lisboa, Portugal, 26-28 February 2017We propose a Genetic Algorithm (GA) to address a Green Vehicle Routing Problem (G-VRP). Unlike classic formulations of the VRP, this study aims to minimise the CO 2 emissions per route. The G-VRP is of interest to policy makers who wish to reduce greenhouse gas emissions. The GA is tested on a suite of benchmark, and real-world instances which include road speed and gradient data. Our solution ap- proach incorporates elements of local and population search heuristics. Solutions are compared with routes currently used by drivers in a courier company. Reductions in emissions are achieved without incurring additional operational costs