DSpace Repository :: Browsing by Author "Palma, Cristian D."

Browsing by Author "Palma, Cristian D."

Now showing 1 - 10 of 10

A comparison of optimization models for lumber production planning
(2015) Palma, Cristian D.; Sepúlveda, Héctor; Vergara, Francisco P.
The performance of sawmills is strongly dependent on how logs are sawn into lumber in order to satisfy the customer demands. To do this, sawmill managers have to decide which cutting patterns have to be applied to logs of different dimensions. Optimization models have been proposed to assist decision makers in this process, but only the profit maximization and the cost minimization of the decisions have been considered as the models objective. In this paper, a linear optimization model was formulated to address lumber production planning and applied to a real problem. The current decisions at sawmills were compared with five different objective functions: the two previously mentioned plus waste minimization, log number minimization and production time minimization. Only profit maximization and waste minimization models reported positive economic returns. Although the current decision at sawmills also reported a positive economic return, the same economic result was obtained with significantly fewer resources using the waste minimization model. The effects of the different objectives on the production indicators were discussed
A Multiobjective Model for the Cutting Pattern Problem with Unclear Preferences
(2016) Palma, Cristian D.; Vergara, Francisco P.
The cutting pattern problem has been traditionally approached using single objective optimization models, although the sawmill performance is usually measured using more than a single indicator. One of the shortcoming of using multiobjective approaches is that they need a preference relationship among the objectives, which is difficult to determine in practice, and solutions are very sensitive to these preferences. In this article, we consider different criteria in a sawmill decisionmaking context using a multiobjective linear optimization model and handle the unclear definition of the objective preferences by formulating a robust version of the model. Although the deterministic formulation assumes perfect information of the objective preferences, in the robust formulation we consider that preferences may be different from their estimate. We show that deterministic decisions are more balanced in terms of the different criteria than the traditional single objective models, although their quality is very sensitive to the objective preferences. We also show that robust decisions are also balanced but less sensitive to the preferences. We explore how the level of the different indicators and the cutting decisions are affected when the preferences are unclear.
A Robust Model for Protecting Road-Building and Harvest-Scheduling Decisions from Timber Estimate Errors
(2014) Palma, Cristian D.; Nelson, John D.
Road-building and harvest-scheduling decisions are primarily based on timber estimates and forecasts that are known to contain errors. It has been shown that in the presence of constraints, decisions generated under these conditions are likely to become infeasible. Therefore, solutions are required that can ensure constraint fulfillment despite the estimation errors. We present a robust model formulation of a multiperiod road-building and harvest-scheduling problem in which protection against minimum demand infeasibility is sought despite the existence of timber estimates that are defined as continuous ranges of values instead of point estimates (as is usually the case in this type of problems). We compare the benefits of this robust formulation with those of the traditional deterministic option and explore the tradeoff between the robustness of the solutions and its impact on the objective function. By simulating different scenarios of the timber coefficient realizations, it is shown that the robust approach produces solutions that are less sensitive to errors in the timber estimates at the expense of a slight reduction in the objective function.
An integrated multi-criteria decision analysis and optimization 2 modeling approach to spatially operational road decisions
(2020) Ezzati, Sättar; Palma, Cristian D.; Bettinger, Pete; Eriksson, Ljusk Ola; Awasthi, Anjali
This study developed a generic cost-effective approach for spatially explicit decision support 30 involved in the allocation of road repair treatments under mountainous conditions. The approach 31 begins with an assessment of the existing road conditions in order to identify the extent of 32 environmental impacts and to set rehabilitation priorities in a subjective manner of group 33 decision making. An integer programming model is, therefore, formulated by integrating expert 34 knowledge with operational costs to guide repair schedules and repair regimes required to each 35 segment at the operational planning level. To demonstrate the model performance, we applied it 36 to a case study comprising 289 km of paved roads in the central highlands of the Hyrcanian 37 forests, in the northern part of Iran. Sensitivity of inputs such as weights verification, budgetary 38 limitations, and rehabilitation weights were tested. Results of the subjective analysis showed that 39 76% of the road analyzed in these forests must be prioritized to receive treatments as intended 40 for forest logistic purposes. Incorporating the extent of environmental impacts into operational 41 costs provided an optimal tradeoff curve caused by selecting an appropriate treatment for each 42 segment across the road network. The approach demonstrate here can be used to design detailed 43 alternative solutions for addressing spatially road decisions under various terrain conditions
Assessing the integration of planning instruments for urban land use and water service
(2023) Gonzalez-Mathiesen, Constanza; Palma, Cristian D.; Jara, Cesar; Zapata, Richard
Land-use planning instruments guide development, significantly affecting future water demands. Hence, land-use and water-service planning should be integrated. However, water availability issues in urban areas might indicate that this integration is not happening. To evaluate the integration among planning instruments, we propose a set of indicators to quantify the magnitude of the integration and an appraisal framework for exploring the possible causes of a lack of integration. We apply them to eight settlements in Chile, and we find some inconsistencies between water service and land-use planning instruments. Suggestions are proposed to enable the desired integration.
Characterization of robust solutions of multi-objetive optimization models with uncertain weights: applications in a sawmill
(2018) Palma, Cristian D.
The use of weights in multi-objective problems is one of the simplest ways to include multiple criteria in optimization models, in what is known as a weighted-sum approach. However, the solution to these models is highly dependent on the value of the weights, which is difficult to determine accurately. In this paper, we consider that the weights are defined as intervals of possible values rather than point estimates, and formulate a robust version of the traditional multi-objective optimization model. We explore, through a computational experiment, the effect that the uncertainty in the weights has on the optimal decisions and the levels obtained of the different objectives. Robust solutions favor decisions that produce similar levels of the different objectives and produce more of those objectives for which the weights are more certain. We apply this model to a lumber production problem where, in practice, more than a single performance indicator is pursued, but there is no clear preference relationship among them
Considering Section Balance in an Integer Optimization Model for the Curriculum-Based Course Timetabling Problem
(2020-10) Palma, Cristian D.; Bornhardt, Patrick
University course timetabling is a complex and time-consuming duty that every educational institution faces regularly. It consists of scheduling a set of lectures in predefined time slots so as to avoid student conflicts, meet teacher and room availability, and manage several institution-specific operational rules. In this paper, we schedule courses based on a curriculum, that is, before the students’ registration. Unlike other curriculum-based models, the proposed model considers two practical aspects when managing the conflicts between lectures: (i) it schedules sections of subjects so that each section is evenly likely to be registered by the students, and (ii) it considers the failure rates and periodicity a subject is taught. We present a multi-objective integer programming model that maximizes the use of specific time slots, the symmetry in which the lectures of a course are scheduled during a week, and the flexibility for straggler students to take courses. The model is solved using commercial software, and it is applied to a real course-timetabling problem. We show the advantages of its use by comparing the model’s solution with the actual solution obtained by the manual scheduling.
Modeling Lean and Agile Approaches: A Western Canadian Forest Company Case Study
(01/09/2018) Vergara, Francisco P; Palma, Cristian D.; Nelson, John D.
In the forest supply chain of the coast of British Columbia, the material flows are directed toward the push production of commodity products. This industry has not adopted lean and agile principles due to unclear economic impacts on the supply chain in changing market conditions. We tested the ability of lean and agile principles to improve performance in the coastal integrated forest industry. Mixed integer programming formulations were subject to over-under production capacity, and over-under demand fulfillment penalties to emulate agile, lean, and hybrid manufacturing environments, when solving the planning problem. Assuming that the coastal integrated forest industry performs as a hybrid environment, the profit results of each manufacturing environment were judged. The results show that, opportunities for profit improvement were 11% for adopting an agile environment when demand was stable with low variation and large batches of production. However, profit improvement was non-existent when the same demand attributes apply but with high variation. The opportunities for profit improvement were 12% when an agile environment or lean environment was adopted when demand was stable with low variation and small batches of production. However, opportunities for profit improvements of 15% existed for adopting an agile environment when demand was unstable with high variation and small batches of production
Multiobjective parallel machine scheduling in the sawmill industry using memetic algorithms
(2014) Baesler, Felipe; Palma, Cristian D.
This study presents a multiobjective optimization algorithm that is termed memetic algorithm with compromise search (MACS). This algorithm, proposed by the authors, combines genetic evolution with local search, in the same way as traditional memetic algorithms, but with the use of independent populations for each objective, as well as a mechanism for finding compromise solutions (tradeoffs) via a local search operator. The algorithm was applied to a parallel machine scheduling problem involving a molding production process in the wood industry. The algorithm was compared against four multiobjective techniques available in the literature: the multiobjective genetic algorithm (MOGA), the strength Pareto evolutionary algorithm (SPEA), the non-sorting genetic algorithm II (NSGA II), and multiobjective genetic local search (MOGLS). The proposed approach outperformed the benchmark techniques in most of the test problems based on two objectives of industrial interest: minimization of the maximum completion time (Cmax) and minimization of total tardiness. These objectives are directly related to the productivity of the product and the ability to deliver goods on time.
Multiperiod Optimisation of Irrigated Crops under Different Conditions of Water Availability
(01/10/2018) Kuschel-Otarola, Mathias; Rivera, Diego; Holzapfel, Eduardo; Palma, Cristian D.; Godoy Faúndez, Alex
We propose a nonlinear optimisation model which maximises profits by resource allocation on a monthly time scale, considering a monthly crop yield model. The proposed model was applied to six management scenarios (two seasonal and four monthly), nine conditions of water availability, and two situations of resource availability under Chilean conditions. These situations provided the same seasonal amount of resources, but different distributions over time. The model included improvements in water resource management such as water storage and water transactions, being the latter a monthly decision variable that can increase farmers’ profits. According to our results, monthly scenarios gave high profits, even better with appropriate resource distribution. When water costs are high, water transactions allow loss reduction of up to 50%. Regarding labour, the lack of availability is more critical than the wages

Browsing by Author "Palma, Cristian D."

Results Per Page

Sort Options