Optimization of Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem by Improved Genetic Algorithm

In order to reduce the distribution cost of fresh food logistics and achieve the goal of green distribution at the same time, the Green Fresh Food Logistics with Heterogeneous Fleet Vehicle Route Problem (GFLHF-VRP) model is established. Based on the particularity of the model, an improved genetic algorithm called Genetic Algorithm with Adaptive Simulated Annealing Mutation (GAASAM) is proposed in which the mutation operation is upgraded to a simulated annealing mutation operation and its parameters are adjusted by the adaptive operation. The experimental results show that the proposed GAASAM can effectively solve the vehicle routing problem of the proposed model, achieve better performance than the genetic algorithm, and avoid falling into a local optimal trap. The distribution routes obtained by GAASAM are with lower total distribution cost, and achieve the goal of green distribution in which energy, fuel consumption and carbon emissions are reduced at the same time. On the other hand, the proposed GFLHF-VRP and GAASAM can provide a reliable distribution route plan for fresh food logistics enterprises with multiple types of distribution vehicles in real life, which can further reduce the distribution cost and achieve a greener and more environment-friendly distribution solution. The results of this study also provide a managerial method for fresh food logistics enterprises to effectively arrange the distribution work with more social responsibility.

Optimization of Earthwork Allocation Path as Vehicle Route Problem Based on Genetic Algorithm

In civil engineering, earthwork, prior to the construction of most engineering projects, is a lengthy and time-consuming work involving iterative processes. The cost of many AEC (Architecture, Engineering and Construction) projects is highly dependent on the efficiency of earthworks (e.g. road, embankment, railway and slope engineering). Therefore, designing proper earthwork planning is of importance. This paper simplifies the earthwork allocation problem to Vehicle Route Problem (VRP) which is commonly discussed in the field of transportation and logistics. An optimization model for the earthwork allocation path based on the modified Genetic Algorithm with a self-adaptive mechanism is developed to work out the global optimal hauling path for earthwork. The research results also instruct the initial topographic shaping of the Winter Olympic Skiing Courses Project. Furthermore, this optimization model is highly compatible with other evolutionary algorithms due to its flexibility, therefore, further improvement in this model is feasible and practical.

Pengembangan Varian Model Vehicle Route Problem (VRP) Untuk Penentuan Rute Angkutan Laut Penumpang Studi Kasus Pt. Pelni (Persero)

Penelitian ini bertujuan mengembangkan varian modelVRP untuk menyusun rute angkutan umum penumpang. Sebagai bahan pertimbangan adalah karakteristik rutenya tertutup yang berawal dan berakhir pada terminal atau pangkalan yang sama, karakteristik pelanggannya deterministik dengan volume permintaan layanan tetap dan dalam kurun waktu saturound trip tertentu, serta karakteristik kendaraan yang dioperasikan memiliki variasi kapasitas dan biaya operasi. Rute disusun untuk memperoleh efisiensi biaya operasional yang optimal, setiap jalur yang ada dalam jaringan pelayanan dilewati tepat satu kali dengan alasan pemberian frekuensi layanan yang sama untuk setiaplink pergerakan penumpang. Penyusunan rute dilakukan melalui dua tahap, yaitu tahap inisialisasi dengan pendekatan metoda Nearest Addition atau Nearest Neighborhood Heuristic dan tahap perbaikan dengan pendekatan metoda Genetic Algorithm. Model ini belum mempertimbangkan adanya pola rute dengan naik-turun penumpang yang dinamis, serta kecepatan dan waktu tempuh kendaraan yang bersifat stokastik, permintaan pergerakan penumpang setiap jalur yang bersifat stokastik, ataupun jumlah pelabuhan dalam jaringan pelayanan yang bersifat stokastik. Sehingga membuka peluang penelitian lebih lanjut. Hasil penelitian menunjukkan bahwa dengan penyusunan ulang rute pelayanan kapal-kapal milik PELNI, total biaya operasional seluruh kapal dapat ditekan jauh lebih efisien hingga mencapai 64,38% dari total biaya aktual. Sedangkan dari sisi total jarak tempuh, dapat ditekan lebih efektif hingga mencapai 59,64% dari total jarak tempuh aktual. Kata kunci: VRP, angkutan laut penumpang, efisiensi biaya, efektivitas jaringan

Domesticating Homecare Services; Vehicle Route Problem Solver Displaced

<p>This article presents a case study of a vehicle route problem solver in the context of homecare work. Vehicle route problem solvers are technologies that calculate geographically rational driving routes. Primarily framed as tools for financial control, they have been tested in homecare services with good results under controlled circumstances. However, they have not been studied as part of users’ everyday work after implementation. The case study shows how, through processes of domestication, the vehicle route problem solver becomes unable to provide homecare workers with ‘optimal’ driving routes. Additionally, it shows how this ‘malfunction’ renders it understood as inconsequential to the very activities it was designed to support which ultimately leads to its removal from driving route production processes. The results highlight the importance of carefully studying how vehicle route problem solvers and other technologies interact with the everyday lives of those who are meant to benefit from them.</p>

Research on Emergency Supplies Scheduling Problem with Robust Optimization Approach

This paper study multiple warehouses emergency supplies dispatch problem. Emergency dispatch vehicles route problem is different from traditional vehicle route problem, it does not take minimization freight, driving distance or driving total time as the goal, but take a minimization unmet needs and delay time as the goal. We use robust operator to transfer multiple warehouses emergency dispatch model into robust counterpart model, and verifying the correctness of the model with number experiment.