Multifactorial Evolutionary Algorithm For Clustered Minimum Routing Cost Problem

Minimum Routing Cost Clustered Tree Problem (CluMRCT) is applied in various fields in both theory and application. Because the CluMRCT is NP-Hard, the approximate approaches are suitable to find the solution for this problem. Recently, Multifactorial Evolutionary Algorithm (MFEA) has emerged as one of the most efficient approximation algorithms to deal with many different kinds of problems. Therefore, this paper studies to apply MFEA for solving CluMRCT problems. In the proposed MFEA, we focus on crossover and mutation operators which create a valid solution of CluMRCT problem in two levels: first level constructs spanning trees for graphs in clusters while the second level builds a spanning tree for connecting among clusters. To reduce the consuming resources, we will also introduce a new method of calculating the cost of CluMRCT solution. The proposed algorithm is experimented on numerous types of datasets. The experimental results demonstrate the effectiveness of the proposed algorithm, partially on large instance

Alternative-fuel station network design under impact of station failures

In this paper, we have formulated a mixed-integer non-linear programming model for alternative-fuel station location problem in which each station can fail with a site-specific probability. The model aims to maximise the total expected traffic volume that can be refuelled by the unreliable alternative-fuel stations. Based on the linearisation techniques, i.e., probability chains and piecewise-linear functions, we linearise the non-linearity of compound probability terms in the non-linear model to solve this problem efficiently. An efficient Tabu search algorithm is also developed to solve the large-size instances. In addition, we extend the model to deal with reliable multi-period alternative-fuel station network design. Computational experiments, carried out on the well-known benchmark instances where the probability of station failures is uniformly generated, show that the proposed models and algorithm can obtain the optimal solutions within a reasonable computation time. Compared to a standard station location model that disregards the potential for station failures, our model designs more reliable alternative-fuel station network under risk of station failures. A sensitivity analysis of failure probabilities in the station network design is investigated to demonstrate the robustness of our model and study how variability in the probability of station failure affects solution robustness

Minimizing total cost of home energy consumption under uncertainties

long with the development of renewable energy sources, energy storage units are introduced to increase the stability and reliability of electricity production. The storage units can improve the efficiency of energy consumption for consumers as well. By smartly controlling home appliances, renewable energy sources and energy storage units, consumers can satisfy their energy demand with a minimum cost. However, the declined maximum capacity of energy storage units and the unstable power of electricity grid, due to randomly unexpected failures, can cause challenges for consumers’ energy plans. In this article, we develop a novel joint chance-constraint mixed-integer linear programming model to support consumers in finding the optimal energy plans for a minimum cost of energy consumption under the simultaneous impact of unexpected failures on energy storage units and electricity grid. A case study for a set of households in Nottingham, United Kingdom, is used to demonstrate the efficiency of the proposed model. Some interesting insights are achieved for home energy management under uncertainties

EROSION FEATURES ALONG CUA DAI BEACH, HOI AN CITY, QUANG NAM PROVINCE, VIETNAM

Hoi An is a famous tourist city in Central Vietnam with Cua Dai beach which is a long beautiful swimming beach. In recent years, tourism of the city is developing very fast. The southern part of Cua Dai beach was covered by many resorts which were located close to the beach and protected by hard structures such as seawall, revetment, groin,… At present, all properties closed to the beach and hard protection structures of resort system were destroyed by wave action. And the northern part of Cua Dai beach (public beach) was seriously eroded and has been protected by “Soft structure”. Cua Dai coast erosion problem becomes the hot topic in communication system from central to local governments and it becomes the big concern of Vietnamese and international scientists. This paper presents the initial study results of Cua Dai beach erosion features. Study results show that Cua Dai beach erosion/deposition phenomenon occurred for a long time but the rate of accretion was larger than that of erosion. From the year of 2000 to present the rate of erosion was larger than that of accretion. The main causes of Cua Dai beach erosion are the interaction between hard protection structures and wave action, dredging operation in Thu Bon river mouth... which reduced the longshore sediment transport rate from Thu Bon river mouth to eroded beach

Models and Heuristics for the Flow-Refuelling Location Problem

Purpose of this paper: Firstly, the paper serves as an overview of the emerging field of flow-refuelling location, which mainly occurs in the context of locating alternative-fuel (hydrogen, electric, liquefied natural gas and hybrid) vehicle refuelling stations. We aim to review and explain models and solution approaches, with a particular focus on mathematical programming formulations. Secondly, we propose a new heuristic for this problem and investigate its performance. Design/methodology/approach: The subject scope of this paper is the flow-refuelling location model (FRLM). While in most location problems demand arises at customer locations, in so-called flow-capturing models it is associated with journeys (origin-destination pairs). What makes the FRLM even more challenging is that due to the limited driving range of alternative-fuel vehicles, more than one facility may be required to satisfy the demand of a journey. There are currently very few such refuelling stations, but ambitious plans exist for massive development – making this an especially ripe time for researchers to investigate this problem. There already exists a body of work on this problem; however different authors make different model assumptions, making comparison difficult. For example, in some models facilities must lie on the shortest route from origin to destination, while in others detours are allowed. We aim to highlight difference in models in our review. Our proposed methodology is built on the idea of solving the relaxation of the mixed-integer linear programming formulation of the problem, identifying promising variables, fixing their values and solving the resulting (so-called restricted) problems optimally. It is somewhat similar to Kernel Search which has recently gained popularity. We also use a parallel computing strategy to simultaneously solve a number of restricted problems with less computation effort for large-sized instances. Findings: Our experimental results show that the proposed heuristic can find optimal solutions in a reasonable amount of time, outperforming other heuristics from the literature. Value: We believe the paper is of value to both academics and practitioners. The review should help researchers new to this field to orient themselves in the maze of different problem versions, while helping practitioners identify models and approaches applicable to their particular problem. The heuristic proposed can be directly used by practitioners; we hope it will spark further works on this area of logistics but also on other optimisation problems where Kernel Search type methods can be applied. Research limitations: This being the first paper applying a restricted-subproblem approach to this problem it is necessarily limited in scope. Applying a traditional Kernel Search method would be an interesting next step. The proposed heuristic should also be extended to cover for more than just one FRLM model: certainly the capacitated FRLM, the FRLM with deviation, the fixed-charge FRLM and the multi-period FRLM should be investigated. Practical implications: Our work adds to a body of research that can inform decisionmakers at governmental or international level on strategic decisions relating to the establishment or development of alternative-fuel refuelling station networks

An efficient heuristic algorithm for the alternative-fuel station location problem

We have developed an efficient heuristic algorithm for location of alternative-fuel stations. The algorithm is constructed based on solving the sequence of subproblems restricted on a set of promising station candidates, and fixing a number of the best promising station locations. The set of candidates is initially determined by solving a relaxation model, and then modified by exchanging some stations between the promising candidate set and the remaining station set. A number of the best station candidates in the promising candidate set can be fixed to improve computation time. In addition, a parallel computing strategy is integrated into solving simultaneously the set of subproblems to speed up computation time. Experimental results carried out on the benchmark instances show that our algorithm outperforms genetic algorithm and greedy algorithm. As compared with CPLEX solver, our algorithm can obtain all the optimal solutions on the tested instances with less computation time

ỨNG DỤNG CÔNG NGHỆ VIỄN THÁM VÀ GIS NGHIÊN CỨU QUÁ TRÌNH DỊCH CHUYỂN ĐƯỜNG BỜ VÀ ĐÓNG/MỞ CỬA ĐẦM Ô LOAN (PHÚ YÊN) GIAI ĐOẠN 1965 - 2014

Application of remote sensing and GIS (Geographic Information System) technologies found that: Fluctuation process of shoreline in O Loan lagoon became evident, through which a general picture of the shoreline development in a long time from 1965 - 2014 has been launched. The process of erosion - accretion evolutions occurred time by time. In which, the period from 1965 - 1995 was the process of erosion - accretion and gradual northward movement of O Loan lagoon inlet, with erosion area greater than deposition area. The period after 1995 was the process of erosion and An Hai inlet opening during rainy season, coincident with northeast monsoon and typhoon activity; and the process of accretion and An Hai inlet closing during dry season, coincident with southwest monsoon.Trên cơ sở ứng dụng công nghệ viễn thám và GIS (hệ thông tin địa lý) cho thấy: Quá trình biến động của đường bờ biển khu vực đầm Ô Loan được thể hiện rõ rệt, qua đó đã đưa ra bức tranh tổng quát về quá trình phát triển của đường bờ, trong một thời gian dài từ năm 1965 - 2014. Các quá trình xói lở - bồi tụ diễn biến theo thời gian. Trong đó, thời kỳ từ năm 1965 - 1995 là các quá trình xói lở - bồi tụ và dịch chuyển cửa biển đầm Ô Loan dần lên phía bắc, với diện tích bị xói lở lớn hơn diện tích được bồi tụ. Thời kỳ từ sau năm 1995 đến nay là quá trình xói lở và mở cửa biển An Hải chủ yếu xảy ra vào mùa mưa, trùng với thời kỳ gió mùa Đông Bắc và bão hoạt động, còn bồi lấp cửa biển xảy ra vào mùa khô, trùng với thời kỳ gió mùa Tây Nam

ĐẶC ĐIỂM BIẾN ĐỔI HÌNH THÁI ĐỊA HÌNH BÃI BIỂN NHA TRANG, KHÁNH HÒA

This paper has focused on analyzing morphological change features of Nha Trang Beach based on the comparison of different beach profiles which were measured from July 2008 to September 2016 corresponding to the Northeast and Southwest monsoons. Additionally, the sediment transport balance was estimated by the method of equity value curve. Studied results show that the beach profiles were accreted and eroded during Southwest and Northeast monsoons respectively, but due to the shortage of materials supply, the beach has the narrowing trend. In this paper, some effects of the existing works in Nha Trang Beach such as Vinpearl, Navy Port, and hydro-dams in upstream area of Cai river have been also analyzed for estimating sedimentary supply to beach segments.Bài báo phân tích đặc điểm biến đổi hình thái địa hình bãi biển Nha Trang trên cơ sở so sánh các trắc diện địa hình bãi biển, với số liệu đo đạc từ tháng 7/2008 đến tháng 9/2016, cụ thể vào các thời kỳ gió mùa Đông Bắc và gió mùa Tây Nam tại các vị trí cố định. Đồng thời, cán cân trầm tích được tính toán và phân tích bằng phương pháp đường cong đẳng giá trị. Kết quả cho thấy, bãi biển được bồi tụ vào mùa gió Tây Nam và bị xói lở vào mùa gió Đông Bắc. Tuy nhiên, do thiếu hụt bồi tích nên bãi biển có xu thế thu hẹp. Bài báo còn phân tích một số ảnh hưởng của các công trình hiện diện tại bãi biển Nha Trang, như cầu cảng Vinpearl, cảng Hải Quân và các đập chắn trên lưu vực sông Cái khi xét đến nguồn cung cấp vật liệu bồi tích

Formulation and solution technique for agricultural waste collection and transport network design

Agricultural waste management in developing countries has become a challenging issue for rural planners due to the lack of an efficient planning tool. In the countries, farmers burnt agricultural waste at fields after each harvesting season to solve the issue. As a result, it has caused air and water pollution in the rural areas of the countries. In this paper, we present a mixed-integer nonlinear programming model for agricultural waste collection and transport network design that aims to stop burning waste and use the waste to produce bio-organic fertilizer. The model supports rural planners to optimally locate waste storages, and to determine the optimal set of routes for a fleet of vehicles to collect and transport the waste from the storages to the bio-organic fertilizer production facility. In the novel location-assignment-routing problem, the overall objective is to minimize total cost of locating storages, collecting waste from fields and planning vehicle routes. A solution technique is developed to linearise the mixed-integer nonlinear programming model into a model in linear form. In addition, a parallel water flow algorithm is developed to solve efficiently the large-sized instances. The efficiency of the proposed model and algorithm is validated and evaluated on the real case study in Trieu Phong district, Quang Tri province, Vietnam, as well as a set of randomly generated large-sized instances. The results show that our solution approach outperforms the general optimisation solver and tabu search algorithm. Our algorithm can find the optimal or near-optimal solutions for the large-sized instances within a reasonable time