Course scheduling optimization using genetic algorithm and tabu search

Scheduling courses in higher education often face problems, such as the clashes of teachers' schedules, rooms, and students' schedules. This study proposes course scheduling optimization using genetic algorithms and taboo search. The genetic algorithm produces the best generation of chromosomes composed of lecturer, day, and hour genes. The Tabu search method is used for the lecture rooms division. Scheduling is carried out for the Informatics faculty with four study programs, 65 lecturers, 93 courses, 265 lecturer assignments, and 65 classes. The process of generating 265 schedules took 561 seconds without any scheduling clashes. The genetic algorithms and taboo searches can process quite many course schedules faster than the manual method.

Representations about sexuality of people diagnosed late with HIV infection

ABSTRACT Objective: to understand the representations about sexuality of people diagnosed late with HIV infection and its implications in the delayed search for diagnosis. Methods: this is a qualitative study, whose theoretical and methodological framework was Social Representation Theory. The research was carried out with 18 people diagnosed late with HIV infection through an open interview. For data analysis, Structural Narration Analysis was used, with support from MAXQDA 12®. Results: representations about sexuality contributed to delayed diagnosis, such as trust in a fixed partnership, sexual intercourse is natural, sexuality as a taboo, search for pleasure in sexual intercourse, regardless of risks, denial of risk for HIV infection. Final considerations: representations about sexuality participate in a web of stereotypes and riskier ways of living, which contribute to delayed diagnosis. Sexual health education remains necessary and essential throughout people’s lives.

Penentuan Rute Dan Penjadwalan Pengangkutan Sampah di Kota Bandung Wilayah Bandung Barat dengan Menggunakan Tabu Search

Abstract― The route determination Model is commonly known as the Vehicle Routing Problem (VRP), VRP deals with determining the route to produce the best route in problems involving more than one vehicle with a certain capacity to serve a number of customer's point according to their respective demands, one of the main purpose of route determination is to minimize total distances. PD. Kebersihan Kota Bandung has been facing one of the problems related to vehicle routing since the route used for waste transport by the company currently does not pay attention to the location and distance of the TPS to be visited, resulting in a longer total distance of 564, 30 km. With the current routes, the company does not have a definite schedule of trash transport, this problem concern involve for trashbin heap. Therefore, VRP research was conducted to determine the transportation of waste routes in West Bandung area by producing solutions that can be proposed to reduce the total distances. The research was solved using the Tabu Search method, the application of this method requires the initial solution. In this study, the saving and sequential method insertion used to create the initial solution, then the initial solution was done repair by using the Tabu Search algorithm. The result of data processing with taboo Search generates 15 routes with the total mileage for each day of 448.48 km. Total distance generated by Tabu Search resulted in a decline of 115.82 km or give a savings of 20.53% from Total distance with the current route. Based on the route comes from Tabu Search, there is a schedule for garbage transport schedules in the TPS and obtained the total time of service by 15 vehicles on each day of 63.45 hours. Abstrak― Model penentuan rute pada umumnya dikenal dengan Vehicle Routing Problem (VRP), VRP berkaitan dengan penentuan rute untuk menghasilkan rute terbaik dalam permasalahan yang melibatkan lebih dari satu kendaraan dengan kapasitas tertentu untuk melayani sejumlah titik pelanggan sesuai dengan permintaan masing-masing, tujuan penentuan rute ini salah satunya adalah untuk meminimumkan jarak tempuh. Penentuan rute menjadi salah satu permasalahan PD. Kebersihan Kota Bandung yang bergerak dibidang pengangkutan sampah, karena rute yang digunakan oleh perusahaan saat ini tidak memperhatikan lokasi dan jarak Tempat Pembuangan Sementara (TPS) yang akan dikunjungi, sehingga menghasilkan total jarak tempuh yang lebih jauh yaitu sebesar 564,30 km. Dengan rute yang digunakan saat ini, perusahaan tidak memiliki jadwal pengangkutan sampah secara pasti yang memberikan kekhawatiran timbulnya penumpukan sampah. Oleh karena itu, dilakukan penelitian VRP untuk menentukan rute pengangkutan sampah diwilayah Bandung Barat dengan menghasilkan solusi yang dapat diajukan untuk mengurangi total jarak. Penelitian ini diselesaikan dengan menggunakan metode Tabu Search, penerapan metode ini memerlukan adanya solusi awal. Dalam penelitian ini, metode saving dan sequential insertion yang digunakan untuk membuat solusi awal, selanjutnya solusi awal tersebut dilakukan perbaikan dengan menggunakan algoritma Tabu Search. Hasil pengolahan data dengan Tabu Search menghasilkan 15 rute dengan total jarak tempuh untuk setiap harinya sebesar 448,48 km. Total jarak yang dihasilkan Tabu Search menghasilkan penurunan sebesar 115,82 km atau memberikan penghematan sebesar 20,53% dari total jarak dengan rute saat ini. Berdasarkan rute yang dihasilkan dari Tabu Search, selanjutnya dilakukan penjadwalan pengangkutan sampah disetiap TPS dan memperoleh waktu pelayanan yang dibutuhkan oleh 15 kendaraan setip harinya sebesar 63,45 jam.

ОПТИМІЗАЦІЯ КОМПОЗИЦІЙНИХ ПЛАНІВ ЕКСПЕРИМЕНТУ МЕТОДОМ СТРИБАЮЧИХ ЖАБ

The second order composition plans are using for the construction of quadratic mathematical models of the probed objects and systems. The plans of the ortogonal central composition planning (OCKP) and rotatable central composition planning (RCKP) behave to them. As criteria of optimization of these plans, cost of experiment plan realization, its time of leading through have been chosen.The method and software for optimization in the cost and temporal expenses of second order composition plans with the use of spring-elastic frogs algorithm were developed. Software is realized in S++ language. All necessary calculations were executed on a computer with the processor of Intel Pentium G620 with frequency 2.60 Ghz. A necessary volume of memory is 26 Mb. Amount of factors and cost of factors levels transitions were entered with a keyboard, or set in a file.Realization of spring-elastic frogs method requires the small volume of computer memory and has a high fast-acting decision of task.The analysis of the known methods of synthesis of optimum on cost and temporal expenses composition the second order plans is conducted and its efficiency is rotined in comparison with the followings methods: swarm of particles, taboo-search, branches and scopes, progressive approximation. By developed method and software for optimization of composition the second order plans with the use of spring-elastic frogs’ algorithm it is possible to attain the high winnings as compared to the initial plan of experiment, optimum or near to optimum results by comparison to the methods of swarm of particles, taboo-search, branches and scopes, progressive approximation, and also high fast-acting of decision of task of optimization as compared to the methods of optimization developed before. The capacity of the developed method is tested at research of process of porous material heat treatment, and also modes of maintenance of the technical systems complex.It is proved that for optimization plans of OCKP and RCKP the use of spring-elastic frogs method is expedient. In future the results will be used for application of this method at research of the various technical systems.

Research on Cooperative Scheduling of Automated Quayside Cranes and Automatic Guided Vehicles in Automated Container Terminal

According to previous research studies, automated quayside cranes (AQCs) and automated guided vehicles (AGVs) in automated container terminals have a high potential synergy. In this paper, a collaborative scheduling model for AQCs and AGVs is established and the capacity limitation of the transfer platform on AQCs is considered in the model. The minimum total energy consumption of automated quayside cranes (AQCs) and Automatic Guided Vehicles (AGVs) is taken as the objective function. A two-stage taboo search algorithm is adopted to solve the problem of collaborative scheduling optimization. This algorithm integrates AQC scheduling and AGV scheduling. The optimal solution to the model is obtained by feedback from the two-stage taboo search process. Finally, the Qingdao Port is taken as an example of a data experiment. Ten small size test cases are solved to evaluate the performance of the proposed optimization methods. The results show the applicability of the two-stage taboo search algorithm since it can find near-optimal solutions, precisely and accurately.

APPLICATION OF THE JUMPING FROGS METHOD FOR THE OPTIMIZATION OF THREE-LEVEL PLANS OF A MULTIPLE FACTOR EXPERIMENT

he planning of the experiment allows us to solve the problem of obtaining a mathematical model with minimal cost and time costs. The cost of implementing an experiment is significantly affected by the order of alternating levels of change in factors. Thus, it is required to find a procedure for the implementation of experiments that provides the minimum cost (time) for conducting a multivariate experiment. This task becomes especially relevant when studying long and expensive processes. The purpose of this article is the further development of the methodology of optimal planning of the experiment in terms of cost (time), which includes a set of methods for optimizing the plans of the experiment and hardware and software for their implementation. Object of study: optimization processes for the cost of three-level plans for multivariate experiments. Subject of research: optimization method for cost and time costs of experimental designs based on the use of the jumping frog method. Experimental research methods are widely used to optimize production processes. One of the main goals of the experiment is to obtain the maximum amount of information about the influence of the studied factors on the production process. Next, a mathematical model of the object under study is built. Moreover, it is necessary to obtain these models at the minimum cost and time costs. The design of the experiment allows you to get mathematical models with minimal cost and time costs. For this, a method and software were developed for optimizing three-level plans using the jumping frog method. Three-level plans are used in the construction of mathematical models of the studied objects and systems. An analysis is made of the known methods for the synthesis of three-level plans that are optimal in cost and time costs. The operability of the algorithm was tested when studying the roughness of the silicon surface during deep plasma-chemical etching of MEMS elements. Its effectiveness is shown in comparison with the following methods: swarm of particles, taboo search, branches and borders. Using the developed method and software for optimizing three-level plans using the jumping frog method, one can achieve high winnings compared to the initial experimental plan, optimal or close to optimal results compared to particle swarm, taboo search, branches and borders methods, and also high speed of solving the optimization problem in comparison with previously developed optimization methods for three-level experimental designs.