Mixed Integer Linear Programming as a Method for Evaluation of Location and Number of Buffer Warehouse in PT Petrokimia Gresik Distribution System (Case Study: West Java and Central Java)

2021 ◽  
Vol 0 (3) ◽  
pp. 104
Author(s):  
Iwan Febrianto ◽  
Nurhadi Siswanto
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Distribution System ◽  
Mixed Integer Linear Programming ◽  
Mixed Integer ◽  
West Java ◽  
Central Java

scholarly journals A Mixed Integer Linear Programming Based Load Shedding Technique for Improving the Sustainability of Islanded Distribution Systems

2020 ◽  
Vol 12 (15) ◽  
pp. 6234 ◽  
Author(s):  
Sohail Sarwar ◽  
Hazlie Mokhlis ◽  
Mohamadariff Othman ◽  
Munir Azam Muhammad ◽  
J. A. Laghari ◽  
...  
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Distribution System ◽  
Mixed Integer Linear Programming ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Stability Index ◽  
Load Shedding ◽  
Mixed Integer ◽  
System Frequency

In recent years significant changes in climate have pivoted the distribution system towards renewable energy, particularly through distributed generators (DGs). Although DGs offer many benefits to the distribution system, their integration affects the stability of the system, which could lead to blackout when the grid is disconnected. The system frequency will drop drastically if DG generation capacity is less than the total load demand in the network. In order to sustain the system stability, under-frequency load shedding (UFLS) is inevitable. The common approach of load shedding sheds random loads until the system’s frequency is recovered. Random and sequential selection results in excessive load shedding, which in turn causes frequency overshoot. In this regard, this paper proposes an efficient load shedding technique for islanded distribution systems. This technique utilizes a voltage stability index to rank the unstable loads for load shedding. In the proposed method, the power imbalance is computed using the swing equation incorporating frequency value. Mixed integer linear programming (MILP) optimization produces optimal load shedding strategy based on the priority of the loads (i.e., non-critical, semi-critical, and critical) and the load ranking from the voltage stability index of loads. The effectiveness of the proposed scheme is tested on two test systems, i.e., a 28-bus system that is a part of the Malaysian distribution network and the IEEE 69-bus system, using PSCAD/EMTDC. Results obtained prove the effectiveness of the proposed technique in quickly stabilizing the system’s frequency without frequency overshoot by disconnecting unstable non-critical loads on priority. Furthermore, results show that the proposed technique is superior to other adaptive techniques because it increases the sustainability by reducing the load shed amount and avoiding overshoot in system frequency.

scholarly journals A Mixed Integer Linear Programming Model for the Optimization of Steel Waste Gases in Cogeneration: A Combined Coke Oven and Converter Gas Case Study

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3781
Author(s):  
Sergio García García ◽  
Vicente Rodríguez Montequín ◽  
Henar Morán Palacios ◽  
Adriano Mones Bayo
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Coke Oven ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Integer Linear Programming Model ◽  
Converter Gas

Off-gas is one of the by-products of the steelmaking process. Its potential energy can be transformed into heat and electricity by means of cogeneration. A case study using a coke oven and Linz–Donawitz converter gas is presented. This work addresses the gas allocation problem for a cogeneration system producing steam and electricity. In the studied facility, located in northern Spain, the annual production of the plant requires 95,000 MWh of electrical energy and 525,000 MWh of thermal energy. The installed electrical and thermal power is 20.4 MW and 81 MW, respectively. A mixed integer linear programming model is built to optimize gas allocation, thus maximizing its benefits. This model is applied to a 24-h scenario with real data from the plant, where gas allocation decision-making was performed by the plant operators. Application of the model generated profit in a scenario where there were losses, increasing benefits by 16.9%. A sensitivity analysis is also performed. The proposed model is useful not only from the perspective of daily plant operation but also as a tool to simulate different design scenarios, such as the capacity of gasholders.

scholarly journals Mixed Integer Linear Programming Models to Solve a Real-Life Vehicle Routing Problem with Pickup and Delivery

2021 ◽  
Vol 11 (20) ◽  
pp. 9551
Author(s):  
Ali Louati ◽  
Rahma Lahyani ◽  
Abdulaziz Aldaej ◽  
Racem Mellouli ◽  
Muneer Nusir
Keyword(s):  
Linear Programming ◽  
Vehicle Routing ◽  
Integer Linear Programming ◽  
Vehicle Routing Problem ◽  
Mixed Integer Linear Programming ◽  
Real Life ◽  
Mixed Integer ◽  
Pickup And Delivery ◽  
Routing Problem

This paper presents multiple readings to solve a vehicle routing problem with pickup and delivery (VRPPD) based on a real-life case study. Compared to theoretical problems, real-life ones are more difficult to address due to their richness and complexity. To handle multiple points of view in modeling our problem, we developed three different Mixed Integer Linear Programming (MILP) models, where each model covers particular constraints. The suggested models are designed for a mega poultry company in Tunisia, called CHAHIA. Our mission was to develop a prototype for CHAHIA that helps decision-makers find the best path for simultaneously delivering the company’s products and collecting the empty boxes. Based on data provided by CHAHIA, we conducted computational experiments, which have shown interesting and promising results.

Multi-criteria decision analysis for pharmaceutical supplier selection problem using fuzzyTOPSIS

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Umar Muhammad Modibbo ◽  
Musa Hassan ◽  
Aquil Ahmed ◽  
Irfan Ali
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Pharmaceutical Company ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Supplier Selection ◽  
Mixed Integer ◽  
Pharmaceutical Companies ◽  
Content Type

PurposeSupplier selection in the supply chain network (SCN) has strategic importance and involves multiple factors. The multi-criteria nature of the problem coupled with environmental uncertainty requires several procedures and considerations. The issue of decision-making in selecting the best among various qualified suppliers remains the major challenge in the pharmaceutical industry. This study investigated the multi-criteria multi-supplier decision-making process and proposed a model for supplier selection problems based on mixed-integer linear programming.Design/methodology/approachThe concept of principal component analysis (PCA) was used to reduce data dimensionality, and the four best criteria have been considered and selected. The result is subjected to decision-makers’ (DMs’) reliability test using the concept of a triangular fuzzy number (TFN). The importance of each supplier to each measure is established using fuzzy technique for order preference by similarity to an ideal solution approach, and the suppliers have ranked accordingly.FindingsThis study proposes a mixed integer linear programming model for supplier selection in a pharmaceutical company. The effectiveness of the proposed model has been demonstrated using a numerical example. The solution shows the model's applicability in making a sound decision in pharmaceutical companies in the space of reality. The model proposed is simple. Readily commercial packages such as LINDO/LINGO and GAMS can solve the model.Research limitations/implicationsThis research contributed to the systematic manner of supplier selection considering DMs’ value judgement under a fuzzy environment and is limited to the case study area. However, interested researchers can apply the study in other related manufacturing industries. However, the criteria have to be revisited to suit that system and might require varying ratings based on the experts' opinions in that field.Practical implicationsThis work suggests more insights practically by considering a realistic and precise investigation based on a real-life case study of pharmaceutical companies with six primary criteria and twenty-four sub-criteria. The study outcome will assist organizations and managers in conducting the best decision objectively by selecting the best suppliers with their various standards and terms among many available contenders in the manufacturing industry.Originality/valueIn this paper, the authors attempted to identify the most critical attributes to be preserved by the top managers (DMs) while selecting suppliers in pharmaceutical companies. The study proposed an MILP model for supplier selection in the pharmaceutical company using fuzzy TOPSIS.

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