V.Jorge Leon - Academia.edu (original) (raw)
Papers by V.Jorge Leon
Planning in Controlled Ecological Life Support Systems (CELSS) requires special lookahead capabil... more Planning in Controlled Ecological Life Support Systems (CELSS) requires special lookahead capabilities due to the complex and long-term dynamic behavior of biological systems. This project characterizes the behavior of CELSS, identifies the requirements of intelligent planning systems for CELSS, proposes the decomposition of the planning task into short-term and long-term planning, and studies the crop scheduling problem as an initial approach to long-term planning. CELSS is studied in the realm of Chaos. The amount of biomass in the system is modeled using a bounded quadratic iterator. The re.suits suggests that closed ecological systems can exhibit periodic behavior when imposed external or artificial control. The main charaeterist_ of CELSS from the plaaning and sclaaleliag perspective are discussed and requirements for planning systems are given. Crop scheduling problem is identified as an important component of the required long-term lookahead capabilities of a CELSS planner. The main charactmi_cs of crop scheduling are described and a model is proposed to represent the problem. A surrogate measure of the probability of survival is developed. The measure reflects the absolute deviation of the vital reservoir levels from their nominal values. The solution space is generated using a probability distribution which captures both knowledge about the system and the current state of affairs at each decision epoch. This probability distribution is used in the context of an evolution paxadigm. The concepts developed serve as the basis for the development of a simple crop scheduling tool which is used to demonstrate its usefulness in the design and operation of CH.e.
Industrial innovation series, Sep 8, 2009
Informs Journal on Computing, 2020
This paper deals with a class of biobjective mixed binary linear programs having a multiple-choic... more This paper deals with a class of biobjective mixed binary linear programs having a multiple-choice constraint, which are found in applications such as Pareto set-reduction problems, single-supplier selection, and investment decisions, among others. Two objective space-search algorithms are presented. The first algorithm, termed line search and linear programming filtering, is a two-phase procedure. Phase 1 searches for supported Pareto outcomes using the parametric weighted sum method, and Phase 2 searches for unsupported Pareto outcomes by solving a sequence of auxiliary mixed binary linear programs. An effective linear programming filtering procedure excludes any previous outcomes found to be dominated. The second algorithm, termed linear programming decomposition and filtering, decomposes the mixed binary problem by iteratively fixing binary variables and uses the linear programming filtering procedure to prune out any dominated outcomes. Computational experiments show the effectiveness of the linear programming filtering and suggest that both algorithms run faster than existing general-purpose objective space-search procedures.
... McCauley-Bush & Lesia L. Crumpton-Young Handbook of Indus... more ... McCauley-Bush & Lesia L. Crumpton-Young Handbook of Industrial Engineering Calculations and Practice Adedeji B. Badiru & Olufemi A. Omitaomu Industrial Control Systems: Mathematical and Statistical Models and Techniques Adedeji B. Badiru, Oye Ibidapo-Obe, & ...
Applied Energy, 2016
This paper deals with the electricity generation capacity expansion problem to minimize cost and ... more This paper deals with the electricity generation capacity expansion problem to minimize cost and water withdrawal. Each solution prescribes locations and technologies for new power plants, and their designed capacities. A two-stage methodology is proposed to aid decision making by identifying the few alternatives from the many efficient solutions that are robust to uncertainties. The first stage finds solutions that are efficient in view of cost and water withdrawal objectives. The second stage finds the subset of first-stage solutions that are robust when the designed capacities of power plants are subjected to uncertainties at the time of their construction. The methodology is applied in a case study for the electrical grid in Texas, USA. The trade-off among technologies and locations, and the effect of uncertainty are considered to answer strategic questions for expansion planning. Experimental results suggest that the methodology prescribes locations, capacities and type of technologies for new power plants in Texas that tend to maintain their prescribed values of cost and water withdrawal when facing unforeseen implementation conditions, while satisfying the required generation capacity.
Planning in Controlled Ecological Life Support Systems (CELSS) requires special lookahead capabil... more Planning in Controlled Ecological Life Support Systems (CELSS) requires special lookahead capabilities due to the complex and long-term dynamic behavior of biological systems. This project characterizes the behavior of CELSS, identifies the requirements of intelligent planning systems for CELSS, proposes the decomposition of the planning task into short-term and long-term planning, and studies the crop scheduling problem as an initial approach to long-term planning. CELSS is studied in the realm of Chaos. The amount of biomass in the system is modeled using a bounded quadratic iterator. The re.suits suggests that closed ecological systems can exhibit periodic behavior when imposed external or artificial control. The main charaeterist_ of CELSS from the plaaning and sclaaleliag perspective are discussed and requirements for planning systems are given. Crop scheduling problem is identified as an important component of the required long-term lookahead capabilities of a CELSS planner. The main charactmi_cs of crop scheduling are described and a model is proposed to represent the problem. A surrogate measure of the probability of survival is developed. The measure reflects the absolute deviation of the vital reservoir levels from their nominal values. The solution space is generated using a probability distribution which captures both knowledge about the system and the current state of affairs at each decision epoch. This probability distribution is used in the context of an evolution paxadigm. The concepts developed serve as the basis for the development of a simple crop scheduling tool which is used to demonstrate its usefulness in the design and operation of CH.e.
Industrial Innovation, 2009
Applied Energy, 2016
This paper deals with the electricity generation capacity expansion problem to minimize cost and ... more This paper deals with the electricity generation capacity expansion problem to minimize cost and water withdrawal. Each solution prescribes locations and technologies for new power plants, and their designed capacities. A two-stage methodology is proposed to aid decision making by identifying the few alternatives from the many efficient solutions that are robust to uncertainties. The first stage finds solutions that are efficient in view of cost and water withdrawal objectives. The second stage finds the subset of first-stage solutions that are robust when the designed capacities of power plants are subjected to uncertainties at the time of their construction. The methodology is applied in a case study for the electrical grid in Texas, USA. The trade-off among technologies and locations, and the effect of uncertainty are considered to answer strategic questions for expansion planning. Experimental results suggest that the methodology prescribes locations, capacities and type of technologies for new power plants in Texas that tend to maintain their prescribed values of cost and water withdrawal when facing unforeseen implementation conditions, while satisfying the required generation capacity.
European Journal of Operational Research, 2016
In this article, an exact method is proposed to optimize two preference functions over the effici... more In this article, an exact method is proposed to optimize two preference functions over the efficient set of a multiobjective integer linear program (MOILP). This kind of problems arises whenever two associated decisionmakers have to optimize their respective preference functions over many efficient solutions. For this purpose, we develop a branch-and-cut algorithm based on linear programming, for finding efficient solutions in terms of both preference functions and MOILP problem, without explicitly enumerating all efficient solutions of MOILP problem. The branch and bound process, strengthened by efficient cuts and tests, allows us to prune a large number of nodes in the tree to avoid many solutions. An illustrative example and an experimental study are reported.
Industrial Innovation, 2009
This paper describes an integrated planning, scheduling and control architecture for robotics and... more This paper describes an integrated planning, scheduling and control architecture for robotics and advanced life support systems. The distinctive characteristics of controlled ecologies and the requirements for planning, scheduling and control architectures are presented. Next, the main components of the proposed architecture are described, and the interaction among the user, the intelligent planner, the generic scheduler, and the crop planner and scheduler is illustrated with a hypothetical scenario. Some successful implementations of components of the architecture and current e orts are also mentioned.
This paper studies binary linear programming problems in the presence of uncertainties that may c... more This paper studies binary linear programming problems in the presence of uncertainties that may cause solution values to change during implementation. This type of uncertainty, termed implementation uncertainty, is modeled explicitly affecting the decision variables rather than model parameters. The binary nature of the decision variables invalidates the use of the existing models for this type of uncertainty. The robust solutions obtained are optimal for a worst-case min-max objective and allow a controlled degree of infeasibility with respect to the associated deterministic problem. Structural properties are used to reformulate the problem as a mixed-integer linear binary program. The degree of solution conservatism is controlled by combining both constraint relaxation and cardinality-constrained parameters. Solutions for optimization problems under implementation uncertainty consist of a set of robust solutions; the selection of solutions from this possibly large set is formulate...
This paper describes an integrated planning schedul ing and control architecture for robotics and... more This paper describes an integrated planning schedul ing and control architecture for robotics and advanced life support systems The distinctive characteristics of controlled ecologies and the requirements for plan ning scheduling and control architectures are pre sented Next the main components of the proposed architecture are described and the interaction among the user the intelligent planner the generic scheduler and the crop planner and scheduler is illustrated with a hypothetical scenario Some successful implemen tations of components of the architecture and current e orts are also mentioned
Planning in Controlled Ecological Life Support Systems (CELSS) requires special lookahead capabil... more Planning in Controlled Ecological Life Support Systems (CELSS) requires special lookahead capabilities due to the complex and long-term dynamic behavior of biological systems. This project characterizes the behavior of CELSS, identifies the requirements of intelligent planning systems for CELSS, proposes the decomposition of the planning task into short-term and long-term planning, and studies the crop scheduling problem as an initial approach to long-term planning. CELSS is studied in the realm of Chaos. The amount of biomass in the system is modeled using a bounded quadratic iterator. The re.suits suggests that closed ecological systems can exhibit periodic behavior when imposed external or artificial control. The main charaeterist_ of CELSS from the plaaning and sclaaleliag perspective are discussed and requirements for planning systems are given. Crop scheduling problem is identified as an important component of the required long-term lookahead capabilities of a CELSS planner. The main charactmi_cs of crop scheduling are described and a model is proposed to represent the problem. A surrogate measure of the probability of survival is developed. The measure reflects the absolute deviation of the vital reservoir levels from their nominal values. The solution space is generated using a probability distribution which captures both knowledge about the system and the current state of affairs at each decision epoch. This probability distribution is used in the context of an evolution paxadigm. The concepts developed serve as the basis for the development of a simple crop scheduling tool which is used to demonstrate its usefulness in the design and operation of CH.e.
Industrial innovation series, Sep 8, 2009
Informs Journal on Computing, 2020
This paper deals with a class of biobjective mixed binary linear programs having a multiple-choic... more This paper deals with a class of biobjective mixed binary linear programs having a multiple-choice constraint, which are found in applications such as Pareto set-reduction problems, single-supplier selection, and investment decisions, among others. Two objective space-search algorithms are presented. The first algorithm, termed line search and linear programming filtering, is a two-phase procedure. Phase 1 searches for supported Pareto outcomes using the parametric weighted sum method, and Phase 2 searches for unsupported Pareto outcomes by solving a sequence of auxiliary mixed binary linear programs. An effective linear programming filtering procedure excludes any previous outcomes found to be dominated. The second algorithm, termed linear programming decomposition and filtering, decomposes the mixed binary problem by iteratively fixing binary variables and uses the linear programming filtering procedure to prune out any dominated outcomes. Computational experiments show the effectiveness of the linear programming filtering and suggest that both algorithms run faster than existing general-purpose objective space-search procedures.
... McCauley-Bush & Lesia L. Crumpton-Young Handbook of Indus... more ... McCauley-Bush & Lesia L. Crumpton-Young Handbook of Industrial Engineering Calculations and Practice Adedeji B. Badiru & Olufemi A. Omitaomu Industrial Control Systems: Mathematical and Statistical Models and Techniques Adedeji B. Badiru, Oye Ibidapo-Obe, & ...
Applied Energy, 2016
This paper deals with the electricity generation capacity expansion problem to minimize cost and ... more This paper deals with the electricity generation capacity expansion problem to minimize cost and water withdrawal. Each solution prescribes locations and technologies for new power plants, and their designed capacities. A two-stage methodology is proposed to aid decision making by identifying the few alternatives from the many efficient solutions that are robust to uncertainties. The first stage finds solutions that are efficient in view of cost and water withdrawal objectives. The second stage finds the subset of first-stage solutions that are robust when the designed capacities of power plants are subjected to uncertainties at the time of their construction. The methodology is applied in a case study for the electrical grid in Texas, USA. The trade-off among technologies and locations, and the effect of uncertainty are considered to answer strategic questions for expansion planning. Experimental results suggest that the methodology prescribes locations, capacities and type of technologies for new power plants in Texas that tend to maintain their prescribed values of cost and water withdrawal when facing unforeseen implementation conditions, while satisfying the required generation capacity.
Planning in Controlled Ecological Life Support Systems (CELSS) requires special lookahead capabil... more Planning in Controlled Ecological Life Support Systems (CELSS) requires special lookahead capabilities due to the complex and long-term dynamic behavior of biological systems. This project characterizes the behavior of CELSS, identifies the requirements of intelligent planning systems for CELSS, proposes the decomposition of the planning task into short-term and long-term planning, and studies the crop scheduling problem as an initial approach to long-term planning. CELSS is studied in the realm of Chaos. The amount of biomass in the system is modeled using a bounded quadratic iterator. The re.suits suggests that closed ecological systems can exhibit periodic behavior when imposed external or artificial control. The main charaeterist_ of CELSS from the plaaning and sclaaleliag perspective are discussed and requirements for planning systems are given. Crop scheduling problem is identified as an important component of the required long-term lookahead capabilities of a CELSS planner. The main charactmi_cs of crop scheduling are described and a model is proposed to represent the problem. A surrogate measure of the probability of survival is developed. The measure reflects the absolute deviation of the vital reservoir levels from their nominal values. The solution space is generated using a probability distribution which captures both knowledge about the system and the current state of affairs at each decision epoch. This probability distribution is used in the context of an evolution paxadigm. The concepts developed serve as the basis for the development of a simple crop scheduling tool which is used to demonstrate its usefulness in the design and operation of CH.e.
Industrial Innovation, 2009
Applied Energy, 2016
This paper deals with the electricity generation capacity expansion problem to minimize cost and ... more This paper deals with the electricity generation capacity expansion problem to minimize cost and water withdrawal. Each solution prescribes locations and technologies for new power plants, and their designed capacities. A two-stage methodology is proposed to aid decision making by identifying the few alternatives from the many efficient solutions that are robust to uncertainties. The first stage finds solutions that are efficient in view of cost and water withdrawal objectives. The second stage finds the subset of first-stage solutions that are robust when the designed capacities of power plants are subjected to uncertainties at the time of their construction. The methodology is applied in a case study for the electrical grid in Texas, USA. The trade-off among technologies and locations, and the effect of uncertainty are considered to answer strategic questions for expansion planning. Experimental results suggest that the methodology prescribes locations, capacities and type of technologies for new power plants in Texas that tend to maintain their prescribed values of cost and water withdrawal when facing unforeseen implementation conditions, while satisfying the required generation capacity.
European Journal of Operational Research, 2016
In this article, an exact method is proposed to optimize two preference functions over the effici... more In this article, an exact method is proposed to optimize two preference functions over the efficient set of a multiobjective integer linear program (MOILP). This kind of problems arises whenever two associated decisionmakers have to optimize their respective preference functions over many efficient solutions. For this purpose, we develop a branch-and-cut algorithm based on linear programming, for finding efficient solutions in terms of both preference functions and MOILP problem, without explicitly enumerating all efficient solutions of MOILP problem. The branch and bound process, strengthened by efficient cuts and tests, allows us to prune a large number of nodes in the tree to avoid many solutions. An illustrative example and an experimental study are reported.
Industrial Innovation, 2009
This paper describes an integrated planning, scheduling and control architecture for robotics and... more This paper describes an integrated planning, scheduling and control architecture for robotics and advanced life support systems. The distinctive characteristics of controlled ecologies and the requirements for planning, scheduling and control architectures are presented. Next, the main components of the proposed architecture are described, and the interaction among the user, the intelligent planner, the generic scheduler, and the crop planner and scheduler is illustrated with a hypothetical scenario. Some successful implementations of components of the architecture and current e orts are also mentioned.
This paper studies binary linear programming problems in the presence of uncertainties that may c... more This paper studies binary linear programming problems in the presence of uncertainties that may cause solution values to change during implementation. This type of uncertainty, termed implementation uncertainty, is modeled explicitly affecting the decision variables rather than model parameters. The binary nature of the decision variables invalidates the use of the existing models for this type of uncertainty. The robust solutions obtained are optimal for a worst-case min-max objective and allow a controlled degree of infeasibility with respect to the associated deterministic problem. Structural properties are used to reformulate the problem as a mixed-integer linear binary program. The degree of solution conservatism is controlled by combining both constraint relaxation and cardinality-constrained parameters. Solutions for optimization problems under implementation uncertainty consist of a set of robust solutions; the selection of solutions from this possibly large set is formulate...
This paper describes an integrated planning schedul ing and control architecture for robotics and... more This paper describes an integrated planning schedul ing and control architecture for robotics and advanced life support systems The distinctive characteristics of controlled ecologies and the requirements for plan ning scheduling and control architectures are pre sented Next the main components of the proposed architecture are described and the interaction among the user the intelligent planner the generic scheduler and the crop planner and scheduler is illustrated with a hypothetical scenario Some successful implemen tations of components of the architecture and current e orts are also mentioned