PERANCANGAN METODE SOLUSI HEURISTIK BAGI MODEL ROLL-ON ROLL-OFF PADA PENJADWALAN TRUK SAMPAH KOTA PONTIANAK

Penelitian terkait penjadwalan truk sampah Kota Pontianak sebelumnya telah  dilakukan oleh Surli (2017). Penelitian tersebut berusaha menyusun penjadwalan kerja bagi truk sampah Kota Pontianak menggunakan model roll-on roll-off. Suatu jadwal kerja bagi truk pengangkut sampah Kota Pontianak yang fisibel dengan kualitas solusi yang cukup baik telah dihasilkan oleh penelitian tersebut. Namun meskipun fisibel, jadwal yang dihasilkan masih mengandung sejumlah unit truk yang melewati batas waktu kerja dengan total kelebihan jam kerja yang cukup tinggi yaitu sebesar 185 menit. Sehingga penelitian ini perlu untuk dilakukan guna mencari solusi yang lebih baik bagi permasalahan tersebut.Penelitian ini mengembangkan metode solusi alternatif berupa algoritma heuristik untuk menyelesaikan permasalahan penjadwalan truk yang menggunakan model Roll-On Roll-Off Vehicle Routing Problem. Algoritma heuristik tersebut diberi istilah Greedy Truck Dispatching (GTD). Algoritma GTD digunakan untuk mencari solusi yang lebih baik daripada solusi yang diberikan oleh penelitian sebelumnya. Algoritma GTD bekerja dengan cara menjadwalkan truk secara “greedy” yaitu menjadwalkan kembali setiap truk yang berstatus iddle paling awal (setelah menyelesaikan suatu rangkaian jadwal kerja) ke jadwal kerja berikutnya jika batas jam kerja belum tercapai. Metode solusi tersebut kemudian diimplementasikan mengunakan bahasa pemrograman Python.Hasil eksekusi dari program telah memberikan  solusi penjadwalan kerja fisible bagi truk sampah yang kualitasnya lebih baik dari penelitian sebelumnya. Dimana pada algoritma GTD ini total kelebihan jam kerja truk yang dijadwalkan berhasil ditekan menjadi hanya sebesar 79 menit.Kata kunci: Greedy, Greedy Truck Dispatching, Roll-On Roll-Off, Vehicle Routing Problem

The Tractor and Semitrailer Routing Considering Carbon Dioxide Emissions

The incorporation of the minimization of carbon dioxide (CO2) emissions in the VRP is important to logistics companies. The paper deals with the tractor and semitrailer routing problem with full truckload between any two depots of the network; an integer programming model with the objective of minimizing CO2 emissions per ton-kilometer is proposed. A two-stage approach with the same core steps of the simulated annealing (SA) in both stages is designed. The number of tractors is provided in the first stage and the CO2 emissions per ton-kilometer are then optimized in the second stage. Computational experiments on small-scale randomly generated instances supported the feasibility and validity of the heuristic algorithm. To a practical-scale problem, the SA algorithm can provide advice on the number of tractors, the routes, and the location of the central depot to realize CO2 emissions decrease

Heterogeneous truck routing policies with tour routing time restriction

We study a heterogeneous full-truckload vehicle routing problem based on the case of a trucking company in Malaysia, where trucks originate from a depot and are dispatched to various parts of the service area. Each order defines an origin-destination pair for pickup and delivery locations. Goods have to be picked up or delivered within the pre-specified pickup and delivery time windows. Besides, we consider a restriction on tour routing time, i.e. the total time taken from the time each truck leaves the depot, servicing a number of orders, to the time it returns to the depot. Our objective is to minimize total deadhead costs. Four integer programming solution policies are proposed. Three of the policies identify the set of homebound trucks before assigning jobs to trucks, while the last policy is a one-off algorithm that assigns job routes to all the trucks and makes sure that each truck will not exceed the total route time limit when it returns to the depot. Crosssectional computation results show that the one-off policy is the best amongst the four. Cumulative analysis results show that all four policies do better than the company’s original assignment in terms of deadhead costs and truck utilization

Waste Collection Vehicle Routing Problem: Literature Review

Waste generation is an issue which has caused wide public concern in modern societies, not only for the quantitative rise of the amount of waste generated, but also for the increasing complexity of some products and components. Waste collection is a highly relevant activity in the reverse logistics system and how to collect waste in an efficient way is an area that needs to be improved. This paper analyzes the major contribution about Waste Collection Vehicle Routing Problem (WCVRP) in literature. Based on a classification of waste collection (residential, commercial and industrial), firstly the key findings for these three types of waste collection are presented. Therefore, according to the model (Node Routing Problems and Arc Routing problems) used to represent WCVRP, different methods and techniques are analyzed in this paper to solve WCVRP. This paper attempts to serve as a roadmap of research literature produced in the field of WCVRP

The Effects of the Tractor and Semitrailer Routing Problem on Mitigation of Carbon Dioxide Emissions

The incorporation of CO2 emissions minimization in the vehicle routing problem (VRP) is of critical importance to enterprise practice. Focusing on the tractor and semitrailer routing problem with full truckloads between any two terminals of the network, this paper proposes a mathematical programming model with the objective of minimizing CO2 emissions per ton-kilometer. A simulated annealing (SA) algorithm is given to solve practical-scale problems. To evaluate the performance of the proposed algorithm, a lower bound is developed. Computational experiments on various problems generated randomly and a realistic instance are conducted. The results show that the proposed methods are effective and the algorithm can provide reasonable solutions within an acceptable computational time

Metaheuristics for the waste collection vehicle routing problem with time windows, driver rest period and multiple disposal facilities

In this problem there is a set of waste disposal facilities, a set of customers at which waste is collected and an unlimited number of homogeneous vehicles based at a single depot.Empty vehicles leave the depot and collect waste from customers, emptying themselves at the waste disposal facilities as and when necessary.Vehicles return to the depot empty.We take into consideration time windows associated with customers, disposal facilities and the depot. We also have a driver rest period.The problem is solved heuristically.A neighbour set is defined for each customer as the set of customers that are close, but with compatible time windows. A procedure that attempts to fully utilise a vehicle is used to obtain an initial solution, with this initial solution being improved using an interchange procedure.We present two metaheuristic algorithms using tabu search and variable neighbourhood search that are based around the neighbour sets.We also present a metaheuristic based on variable neighbourhood tabu search, where the variable neighbourhood is searched via tabu search.Computational results are presented for publicly available waste collection problems involving up to 2092 customers and 19 waste disposal facilities, which indicate that our algorithms produce better quality solutions than previous work presented in the literature

Transportation-mission-based Optimization of Heterogeneous Heavy-vehicle Fleet Including Electrified Propulsion

Commercial-vehicle manufacturers design vehicles to operate over a wide range of transportation tasks and driving cycles. However, certain possibilities of reducing emissions, manufacturing and operational costs from end vehicles are neglected if the target range of transportation tasks is narrow and known in advance, especially in case of electrified propulsion. Apart from real-time energy optimization, vehicle hardware can be meticulously tailored to best fit a known transportation task. As proposed in this study, a heterogeneous fleet of heavy-vehicles can be designed in a more cost- and energy-efficient manner, if the coupling between vehicle hardware, transportation mission, and infrastructure is considered during initial conceptual-design stages. To this end, a rather large optimization problem was defined and solved to minimize the total cost of fleet ownership in an integrated manner for a real-world case study. In the said case-study, design variables of optimization problem included mission, recharging infrastructure, loading--unloading scheme, number of vehicles of each type, number of trips, vehicle-loading capacity, selection between conventional, fully electric, and hybrid powertrains, size of internal-combustion engines and electric motors, number of axles being powered, and type and size of battery packs. This study demonstrated that by means of integrated fleet customization, battery-electric heavy-vehicles could strongly compete against their conventional combustion-powered counterparts. Primary focus has been put on optimizing vehicle propulsion, transport mission, infrastructure and fleet size rather than routing