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en línea para Revistas Científicas de América Latina,
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The Oil Platform Transport Problem is considered as a combination/interlink of the two well-studied NP-Hard/NP-Complete problems: the Helicopter Routing Problem-HRP (a generalization of the Split Delivery Vehicle Routing Problem) and the one-dimensional Bin Packing Problem (BPP-1). The Oil Platform Transport Problem consist of to minimize the cost of carry resources, goods or people from one location (airport/platform) to another location (airport/platform) using helicopters with some restrictions as capacity and time windows. We provide the proof that this problem is NP-Hard/NP-Complete Problem by the polynomial transformation using formal languages between the Vehicle Routing Problem and the Oil Platform Transport Problem. We propose a new mathematical model to the Oil Platform Transport problem, and we present the parameters or characterization of Oil Platform Transport Problem instances of Mexican state-owned petroleum company (PEMEX). We generated 5 instance set, each instance set has 50 cases of randomly generated instances and real instances (with GIS data) of PEMEX Oil Platforms. We use the CPLEX solver to find the optimal cost of carrier resources, goods or people contains in the Oil Platform Transport Problem.  The Oil Platform Transport Problem is considered as a combination/interlink of the two well-studied NP-Hard/NP-Complete problems: the Helicopter Routing Problem-HRP (a generalization of the Split Delivery Vehicle Routing Problem) and the one-dimensional Bin Packing Problem (BPP-1). The Oil Platform Transport Problem consist of to minimize the cost of carry resources, goods or people from one location (airport/platform) to another location (airport/platform) using helicopters with some restrictions as capacity and time windows. We provide the proof that this problem is NP-Hard/NP-Complete Problem by the polynomial transformation using formal languages between the Vehicle Routing Problem and the Oil Platform Transport Problem. We propose a new mathematical model to the Oil Platform Transport problem, and we present the parameters or characterization of Oil Platform Transport Problem instances of Mexican state-owned petroleum company (PEMEX). We generated 5 instance set, each instance set has 50 cases of randomly generated instances and real instances (with GIS data) of PEMEX Oil Platforms. We use the CPLEX solver to find the optimal cost of carrier resources, goods or people contains in the Oil Platform Transport Problem.

Scheduling Activity (SA) is a highly complex optimization problem that is relevant nowdays, both in the private sector and in the public sector. In state of the art are reported several approaches for SA. However, the number of jobs that involve decomposition strategies in their solution is very limited. According to the literature, the decomposition of a problem favors the efficient use of computing resources, improving execution time and reaching competitive solutions compared to those reported in the literature. This paper proposes a new model-based decomposition method, which uses bandwidth minimization algorithms (BMA) in scattered matrices for the generation of angular structures in linear programming models. The study seeks to demonstrate that, depending on the BMA, there is a difference in the results obtained by the proposed method. The results obtained from the proposed experiment demonstrate that there are differences in the decomposition obtained by the method, using two particular heuristics that minimize the bandwidth in scattered matrices. The differences are regarding the reduction in the number of additional variables generated, when the bandwidth is lower. This fact suggests to look for better BMA, and to compare its effects under the proposed method, against other strategies of decomposition.

In 2015, authorities in Cali, Colombia, reported more than 309 deaths in traffic accidents, where 70% of the cases involved motorcycles. These figures generate concern in the city authorities, which leads to the study of alternatives for improving prehospital emergency care. The localization of ambulances iscurrently based on the experience of staff in Medical Emergencies. Thus, the distance between the location of the ambulances and the point of care is considered minimal. This paper presents a localization model todetermine the number of ambulances needed to deal with emergencies reported by the city traffic bureau and its geographical location; different alternatives for improvement are evaluated. The proposed model is based on the expected maximum coverage location problem (MEXCLP), whose objective is to maximize the satisfied demand weighted by the availability of the service, which is calculated through the global estimate of the average occupancy level for each ambulance, based on the geographical and temporal distribution of historical demand. This means that research contributes to maximize coverage of reported emergencies by determining the number of ambulances needed for such care in the City under study. Finally, for its solution, a mathematical programming language and the platform NEOS Server for Optimization (https://neos-server.org/) are used.

This paper summarizes our work towards developing a solution to the Curriculum Based Timetabling Problem (CB-TTP) at a Mexican university and providing significant insights into timetable processing. We first, identified a data structure using a Mediation Software (MS). This software can read, analyze, and organize data from different institutional log files. Additionally, the MS makes groups of courses without interference in the curricula in order to eliminate this constraint of the Integer Programming (IP) model. Then, we present a comprehensive IP model, which use a set of complex constraints, e.g., professor’s availability, consider the course modality in order to assign an appropriate room, consecutive and isolated period of the courses, among others. Also, consider the constraint that ensures do not cancel courses of interest due to parallel assignments of the mandatory courses. With this methodology was possible to assign 2101 lectures and improve the efficiency of the current scheduling process.

The soccer players always have sought to improve its performance. There are methodologies, diets, and an excellent coach to improve the soccer skills. In this paper, we propose the use of metrics or statistical indicators for improving the soccer performance. Additionally we take into consideration the rating of the individual errors with negative points: Goals Shots Off Target, Not goals from direct free-kicks and indirect free-kicks, Unsuccessful dribbles, Caught Opposition Offside, Unsuccessful Shots free-kicks or indirect free-kicks, Head Shots Off the target, Shots Off Target, Unsuccessful Long /short passes, Pass Directions incorrect, Pass Lengths incorrect, Pass Locations incorrect, Duels lost on the offensive/defensive, Aerial duels lost on the offensive/defensive, Own goals, Penalties conceded, Defensive mistakes, Fouls Committed, Corner Crosses / direct or indirect free-kicks conceded, Throw-ins conceded, Yellow or red cards, Substituted off, and others, which significantly affects the soccer performance of the team, to the metric called Motivation Index or lack of motivation. A European soccer match was analyzed to obtain the index of motivation and thereby determine the relationship of the index with the final outcome of the match. We use the NacSports software to perform an analysis of videos of a soccer match.

The goal of this work is to establish and solve the Quadratic As-signation Problem (QAP) as a combinatory optimization problem by means of GRASP (Greedy Randomized Adaptive Search Procedure) as an approximation method to QAP.Applying GRASP to QAP produces good results to obtain solutions close to the optimum or even reach the optimum in several cases. The implementation of a sequential program was successfully made in C. The robustness of GRASP obeys to the inclusions of strategic procedures for each one of the three local search neighborhood structures employed as a second phase of GRASP. Finally a parallel system was built to reduce the time cost of the CPU.

Communication is an important tool for evolutionary robotics. Some important aspects are the emergence of signals, the environment, and manipulation of social and evolutionary variables. In this paper we focus on social aspects related to exploration in poisoned and food environments. These aspects are as follows: a) intermediate levels of heterogeneity in population of evolutionary robots, and b) cooperation of robots for fitness contribution to regulate the emergence of communication signals. The FARSA simulator and Marxbot robot are used in order to optimize the weights of neural networks using a steady state genetic algorithm. A basic communication system is developed based on color LEDs and linear cameras.

This paper aims at being a guide to understand the Farm Production Management (FPM) implementing a new paradigm based on CPLEX method with Project Scheduling Problem (PSP) as an integration of Artificial Intelligence with Project Management. In this proposal we design a mathematical model to represent FPM and the objective function oriented to minimize the resources. In this paper we propose the simulation with random data where the parameters are classified as: crop, land, labor, and water. The declared variables are Amount Planted, Permanent Labor Hired, Temporary Labor Hired, Sales and Fraction Consumed. Restrictions: Land limitations, Labor requirements, Water Requirements and Family Consumptions.

One of the most important tasks in approximately solving an optimisation problem is to adjust the parameters of the metaheuristic used as a solution method. As the metaheuristics are usually general in purpose, it is necessary to make adjustments to them for each optimisation problem to which they are applied to get high-quality solutions. In this paper, we propose the use of a Type 1 Fuzzy Inference System and a Type 2 Fuzzy Logic Inference System to select the operators of a Genetic Algorithm during execution time to solve a set of ten test functions from the literature. The results of computational experiments show that the fuzzy selection of operators improves the performance of the original GA on nine of the ten test functions with practically the same execution time.

The objective is to analyze the economic feasibility under risk conditions of a water solar heating system. Based on economic and environmental data collected in 2014 and 2015 in Hidalgo State (Mexico), two different ways for heating water for domestic use were compared in the region considering the annual cost criteria. The first scenario (deterministic) analyzes a traditional heating system based on LP gas, while the second scenario considers a solar heating system coupled with an LP gas system, this one to be used as an alternative when there is not enough solar radiation. Both scenarios considerate the investment, operation and maintenance costs, however, the second scenario, which is studied by means of a simulation model constructed in @RiskTM, considers the annual days variability with low solar radiation. For a low level hot water demand (2 people), the results showed that the expected value of the annual cost, of the solar system was lower, up to an annual average of 220 days with low solar radiation.  Also, for a high demand level of hot water (8 people), the annual average cost of the solar system was lower, even though, the average days with low solar radiation were approximately 300. As it is known, in the geographical area where the Hidalgo State is located, the average days with low solar radiation ranges from 30 to 40 annually. Therefore, the results show a considerable annually average saving of $ 2,000.00 and $ 10,000.00 MXP, for a low and high demand level respectively.