This paper presents a multiobjective linear integerprogramming model for supporting the choice of remote load control strategies in electric distribution network management. The model takes into account the main conc...
详细信息
This paper presents a multiobjective linear integerprogramming model for supporting the choice of remote load control strategies in electric distribution network management. The model takes into account the main concerns in load management, considering three objective functions: minimization of the peak demand as perceived by the distribution network dispatch center, maximization of the utility profit associated with the energy services delivered by the controlled loads and minimization of the discomfort caused to consumers. The problem was analyzed using an interactive reference point method for multiobjectiveinteger (and mixed-integer) linear programming. This approach exploits the use of the branch-and-bound algorithm for solving the reference point scalarizing programs through which efficient solutions are computed. Post-optimality techniques enable a stability analysis of the efficient solutions by means of computing and displaying graphically sets of reference points that correspond to the same solution. (C) 2006 Elsevier Ltd. All rights reserved.
We consider multi-objective optimization problems where the decision maker (DM) has equity concerns. We assume that the preference model of the DM satisfies properties related to inequity-aversion, hence we focus on f...
详细信息
We consider multi-objective optimization problems where the decision maker (DM) has equity concerns. We assume that the preference model of the DM satisfies properties related to inequity-aversion, hence we focus on finding nondominated solutions in line with the properties of inequity-averse preferences, namely the equitably nondominated solutions. We discuss two algorithms for finding good subsets of equitably nondominated solutions. The first approach is an extension of an interactive approach developed for finding the most preferred nondominated solution when the utility function is assumed to be quasiconcave. We find the most preferred equitably nondominated solution when the utility function is assumed to be symmetric quasiconcave. In the second approach we generate an evenly distributed subset of the set of equitably nondominated solutions to be considered further by the DM. We show the computational feasibility of the two algorithms on equitable multi-objective knapsack problem, in which projects in different categories are to be funded subject to a limited budget. We perform experiments to show and discuss the performances of the algorithms.
We consider split algorithms that partition the objective function space into - 1 dimensional regions so as to search for nondominated points of multiobjective integer programming problems, where is the number of obje...
详细信息
We consider split algorithms that partition the objective function space into - 1 dimensional regions so as to search for nondominated points of multiobjective integer programming problems, where is the number of objectives. We provide a unified approach that allows different split strategies to be used within the same algorithmic framework with minimum change. We also suggest an effective way of making use of the information on subregions when setting the parameters of the scalarization problems used in the -split structure. We compare the performances of variants of these algorithms both as exact algorithms and as solution approaches under time restriction, considering the fact that finding the whole set may be computationally infeasible or undesirable in practice. We demonstrate through computational experiments that while the (-1)-split structure is superior in terms of overall computational time, the-split structure provides significant advantage under time/cardinality limited settings in terms of representativeness, especially with adaptive parameter setting and/or a suitably chosen order for regions to be explored.
This paper considers multiobjective integer programming problems where each coefficient of the objective functions is expressed by a random fuzzy variable. A new decision making model is proposed by incorporating the ...
详细信息
This paper considers multiobjective integer programming problems where each coefficient of the objective functions is expressed by a random fuzzy variable. A new decision making model is proposed by incorporating the concept of probability maximization into a possibilistic programming model. For solving transformed deterministic problems, genetic algorithms with double strings for nonlinear integerprogramming problems are introduced. An interactive fuzzy satisficing method is presented for deriving a satisficing solution to a decision maker by updating the reference probability levels. An illustrative numerical example is provided to clarify the proposed method.
In organizational and academic settings, the strategic formation of teams is paramount, necessitating an approach that transcends conventional methodologies. This study introduces a novel application of multicriteria ...
详细信息
In organizational and academic settings, the strategic formation of teams is paramount, necessitating an approach that transcends conventional methodologies. This study introduces a novel application of multicriteria integerprogramming (MCIP), which simultaneously accommodates multiple criteria, thereby innovatively addressing the complex task of team formation. Unlike traditional single-objective optimization methods, our research designs a comprehensive framework capable of modeling a wide array of factors, including skill levels, backgrounds, and personality traits. The objective function of this framework is optimized to maximize within-team diversity while minimizing both conflict levels and variance in diversity between teams. Central to our approach is a two-stage optimization process. Initially, it segments the population into subgroups using a weighted heterogeneous multivariate K-means algorithm, allowing for a targeted and nuanced team assembly. This is followed by the application of a surrogate optimization technique within these subgroups, efficiently navigating the complexities of MCIP for large-scale applications. Our approach is further enhanced by the inclusion of explicit constraints such as potential interpersonal conflicts, a factor often overlooked in previous studies. The results from our study demonstrate the optimality and robustness of our model across simulation scenarios with different data heterogeneity levels. The contributions of this study are manifold, addressing critical gaps in the existing literature with a theory-backed, empirically validated framework for advanced team formation. Beyond theoretical implications, our work provides a practical guide for implementing conflict-aware, sophisticated team formation strategies in real-world scenarios. This advancement paves the way for future research to explore and enhance this model, providing more sophisticated and efficient team formation strategies.
It is well known that Brazil is the largest producer of sugarcane in the world. Nevertheless, a great concern exists about the crop system used, because the most common practice is manual harvesting with prior straw b...
详细信息
It is well known that Brazil is the largest producer of sugarcane in the world. Nevertheless, a great concern exists about the crop system used, because the most common practice is manual harvesting with prior straw burning. The Brazilian authorities have approved a law prohibiting the burning of sugarcane crop residue before harvesting. However, mechanized harvesting creates the new problem of having to deal with the residue. Many studies have indeed proposed the use of this residue as an energy source. A major difficulty in using this residue is how to economically transport sugarcane harvest biomass from a farm to a processing centre. Besides transport costs, another concern is knowing whether the energy generated by the straw offsets the energy used, in terms of fuel, in the process. This study proposes a multiobjectiveinteger linear programming optimization model to choose sugarcane varieties so as to minimize costs in the use of crop residue and simultaneously maximize the energy balance in such a process. Computational results are presented and discussed.
The paper presents a bi-objective integer program and an approximative lexicographic approach for a bicriterion loading and routing problem in a flexible assembly system. The problem objective is to determine an alloc...
详细信息
The paper presents a bi-objective integer program and an approximative lexicographic approach for a bicriterion loading and routing problem in a flexible assembly system. The problem objective is to determine an allocation of tasks among the assembly stations for a set of products so as to balance station workloads and minimize total interstation transfer time. In the approach proposed, first the station workloads are balanced using a linear relaxation-based heuristic and then assembly routes are selected based on a network flow model. An illustrative example is provided and some results of computational experiments are reported. (C) 1998 Elsevier Science B.V.
This paper presents integerprogramming formulations and an interactive solution procedure for a bicriterion loading problem in a flexible assembly system. The system is made up of a set of assembly stations linked wi...
详细信息
This paper presents integerprogramming formulations and an interactive solution procedure for a bicriterion loading problem in a flexible assembly system. The system is made up of a set of assembly stations linked with an automated material handling system. In the system, several different product types can be assembled simultaneously. The problem objective is to assign assembly tasks and products to stations with limited working space, so as to balance the station workloads and to minimize station-to-station product transfer time, subject to precedence relations among the tasks for a mix of product types. The solution procedure proposed is based on the weighting method and the interactive search for a set of weights which would produce the most preferred nondominated solution. Numerical examples are included to illustrate possible applications of the interactive approach for various problem formulations proposed.
We present a new algorithm for optimizing a linear function over the set of efficient solutions of a multiobjectiveinteger program (MOIP). The algorithm's success relies on the efficiency of a new algorithm for e...
详细信息
We present a new algorithm for optimizing a linear function over the set of efficient solutions of a multiobjectiveinteger program (MOIP). The algorithm's success relies on the efficiency of a new algorithm for enumerating the nondominated points of a MOIP, which is the result of employing a novel criterion space decomposition scheme which (1) limits the number of subspaces that are created, and (2) limits the number of sets of disjunctive constraints required to define the single-objective IP that searches a subspace for a nondominated point. An extensive computational study shows that the efficacy of the algorithm. Finally, we show that the algorithm can be easily modified to efficiently compute the nadir point of a multiobjectiveinteger program. (C) 2016 Elsevier B.V. All rights reserved.
We present an algorithm for triobjective nonlinear integer programs that combines the epsilon\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepacka...
详细信息
We present an algorithm for triobjective nonlinear integer programs that combines the epsilon\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varepsilon $$\end{document}-constrained method with available oracles for biobjective integer programs. We prove that our method is able to detect the nondominated set within a finite number of iterations. Specific strategies to avoid the detection of weakly nondominated points are devised. The method is then used to determine the nondominated solutions of triobjective 0-1 models, built to design nutritionally adequate and healthy diet plans, minimizing their environmental impact. The diet plans refer to menus for school cafeterias and we consider the carbon, water and nitrogen footprints as conflicting objectives to be minimized. Energy and nutrient contents are constrained in suitable ranges suggested by the dietary recommendation of health authorities. Results obtained on two models and on real world data are reported and discussed.
暂无评论