Solving the bi-objective capacitated p -median problem with multilevel capacities using compromise programming and VNS

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.A bi‐objective optimisation using a compromise programming (CP) approach is proposed for the capacitated p‐median problem (CPMP) in the presence of the fixed cost of opening facility and several possible capacities that can be used by potential facilities. As the sum of distances between customers and their facilities and the total fixed cost for opening facilities are important aspects, the model is proposed to deal with those conflicting objectives. We develop a mathematical model using integer linear programming (ILP) to determine the optimal location of open facilities with their optimal capacity. Two approaches are designed to deal with the bi‐objective CPMP, namely CP with an exact method and with a variable neighbourhood search (VNS) based matheuristic. New sets of generated instances are used to evaluate the performance of the proposed approaches. The computational experiments show that the proposed approaches produce interesting results

Formulation and solution of a two-stage capacitated facility location problem with multilevel capacities

In this paper, the multi-product facility location problem in a two-stage supply chain is investigated. In this problem, the locations of depots (distribution centres) need to be determined along with their corresponding capacities. Moreover, the product flows from the plants to depots and onto customers must also be optimised. Here, plants have a production limit whereas potential depots have several possible capacity levels to choose from, which are defined as multilevel capacities. Plants must serve customer demands via depots. Two integer linear programming (ILP) models are introduced to solve the problem in order to minimise the fixed costs of opening depots and transportation costs. In the first model, the depot capacity is based on the maximum number of each product that can be stored whereas in the second one, the capacity is determined by the size (volume) of the depot. For large problems, the models are very difficult to solve using an exact method. Therefore, a matheuristic approach based on an aggregation approach and an exact method (ILP) is proposed in order to solve such problems. The methods are assessed using randomly generated data sets and existing data sets taken from the literature. The solutions obtained from the computational study confirm the effectiveness of the proposed matheuristic approach which outperforms the exact method. In addition, a case study arising from the wind energy sector in the UK is presented

Integrated strategic energy mix and energy generation planning with multiple sustainability criteria and hierarchical stakeholders

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordThis paper proposes a combination of two optimization models for simultaneously determining strategic energy planning at both national and regional levels. The first model deals with a single-period energy mix where the electricity production configuration at a future date (e.g., 2050), based on the available generation sources, is optimally obtained. An optimization model, based on a non-linear goal programming method, is designed to ensure a mixed balance between national and regional goals. The desired energy mix configuration, which is the solution obtained by solving the first model, is then fed into the second model as the main data input. In the second model, a multiple-period generation expansion plan is designed which optimizes the energy transition over the time horizon from the present until the future planning date (2050). The model considers uncertain parameters, including the regional energy demand, fuel cost, and national peak load. A two-stage stochastic programming model is developed where the sample average approximation approach is used as a method of solution. The practical use of the proposed models has been assessed through application to the electricity generation system in China

PENGARUH WHISTLEBLOWING SYSTEM DAN EFEKTIVITAS AUDIT INTERNAL TERHADAP PENCEGAHAN KECURANGAN (FRAUD) (Survey Pada Tiga BUMN di Kota Bandung)

ABSTRAK Penelitian ini bertujuan untuk menguji dan menganalisis seberapa besar pengaruh pelaksanaan whistleblowing system dan efektivitas audit internal terhadap pencegahan kecurangan (fraud). Populasi dalam penelitian ini adalah unit Audit Internal pada Tiga Perusahaan BUMN di Kota Bandung. Jumlah sampel yang diambil sebanyak 61 responden. Metode penelitian yang digunakan adalah metode deskriptif dan verifikatif. Teknik pengumpulan data yang dilakukan melalui data primer dengan kuesioner. Teknik sampling menggunakan sampel jenuh. Analisis statistik yang digunakan dalam penelitian ini yaitu Uji Validitas, Uji Reliabilitas, Regresi Linier Berganda, Analisis Koefisien Korelasi, Uji Hipotesis dan Analisis Koefisien Determinasi. Berdasarkan hasil penelitian dapat diketahui bahwa besarnya pengaruh pelaksanaan whistleblowing system terhadap pencegahan kecurangan yaitu sebesar 33,1% dan besarnya pengaruh efektivitas audit internal terhadap pencegahan kecurangan yaitu sebesar 28,7%. Dengan demikian, semakin tinggi pengaruh pelaksanaan whistleblowing system dan efektivitas audit internal maka akan semakin meningkatkan pencegahan kecurangan. Kata kunci: Whistleblowing System, Efektivitas Audit Internal, Pencegahan Kecurangan (Fraud

PENGARUH PROFITABILITAS, LEVERAGE, DAN LIKUIDITAS TERHADAP AGRESIVITAS PAJAK (Studi Pada Perusahaan SubSektor Transportasi Yang Terdaftar Di Bursa Efek Indonesia Tahun 2016-2018)

ABSTRAK Penelitian ini bertujuan untuk meneliti secara empiris mengenai pengaruh Profitabilitas, Leverage dan Likuiditas terhadap Agresifitas Pajak pada perusahaan SubSektor Transportasi yang terdaftar di Bursa Efek Indonesia Tahun 2016-2018. Teknik Sampling yang digunakan dalam penelitian ini adalah non probability sampling dengan menggunakan pendekatan purposive sampling untuk mengetahui pengaruh Profitabilitas, Leverage dan Likuiditas terhadap Agresivitas Pajak. Penelitian dilakukan dengan metode kuantitatif dan deskriptif, dengan menggunakan sample sebanyak 31 perusahaan SubSektor Transportasi yang terdaftar di Bursa Efek Indonesia Tahun 2016-2018. Teknik analisis data yang dipakai dalam penelitian ini adalah uji hipotesis (uji t), uji linier sederhana, uji koefisiensi korelasi, dan koefisien determinasi. Hasil penelitian ini menunjukkan bahwa Profitabilitas, Leverage, Likuiditas secara Parsial berpengaruh secara signifikan terhadap Agresivitas Pajak pada Perusahaan SubSektor Transportasi yang Terdaftar Di Bursa Efek Indonesia pada Tahun 2016-2018 dengan kontribusi Profitabilitas 40.5%, Leverage 51.9% dan Likuiditas 41.3%. Kata Kunci : Profitabilitas, Leverage, Likuiditas dan Agresivitas Paja

Hybrid Meta-heuristics with VNS and Exact Methods: Application to Large Unconditional and Conditional Vertex p-Centre Problems

Large-scale unconditional and conditional vertex p-centre problems are solved using two meta-heuristics. One is based on a three-stage approach whereas the other relies on a guided multi-start principle. Both methods incorporate Variable Neighbourhood Search, exact method, and aggregation techniques. The methods are assessed on the TSP dataset which consist of up to 71,009 demand points with p varying from 5 to 100. To the best of our knowledge, these are the largest instances solved for unconditional and conditional vertex p-centre problems. The two proposed meta-heuristics yield competitive results for both classes of problems

The incorporation of fixed cost and multilevel capacities into the discrete and continuous single source capacitated facility location problem

In this study we investigate the single source location problem with the presence of several possible capacities and the opening (fixed) cost of a facility that is depended on the capacity used and the area where the facility is located. Mathematical models of the problem for both the discrete and the continuous cases using the Rectilinear and Euclidean distances are produced. Our aim is to find the optimal number of open facilities, their corresponding locations, and their respective capacities alongside the assignment of the customers to the open facilities in order to minimise the total fixed and transportation costs. For relatively large problems, two solution methods are proposed namely an iterative matheuristic approach and VNS-based matheuristic technique. Dataset from the literature is adapted to assess our proposed methods. To assess the performance of the proposed solution methods, the exact method is first applied to small size instances where optimal solutions can be identified or lower and upper bounds can be recorded. Results obtained by the proposed solution methods are also reported for the larger instances

Neighbourhood Reduction in Global and Combinatorial Optimization: The Case of the p-Centre Problem

Neighbourhood reductions for a class of location problems known as the vertex (or discrete) and planar (or continuous) p-centre problems are presented. A brief review of these two forms of the p-centre problem is first provided followed by those respective reduction schemes that have shown to be promising. These reduction schemes have the power of transforming optimal or near optimal methods such as metaheuristics or relaxation-based procedures, which were considered relatively slow, into efficient and exciting ones that are now able to find optimal solutions or tight lower/upper bounds for larger instances. Research highlights of neighbourhood reduction for global and combinatorial optimisation problems in general and for related location problems in particular are also given