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One-to-many two-sided matching decision of logistics O2O platform considering the intermediary benefit

KNOWLEDGE AND INFORMATION SYSTEMS 2025年第1期67卷 689-725页

作者： Deng, Zhibin Yuan, Tao Yue, Qi Liu, Xiaohua Shanghai Univ Engn Sci Sch Management Shanghai 201620 Peoples R China Jiangxi Univ Finance & Econ Sch Informat Management Nanchang 330013 Peoples R China

In existing logistics online-to-offline (O2O) platform decision activities, psychological behavioral behaviors of logistics demanders and suppliers have become increasingly complex, and the required information also involves a great deal of uncertainty and vagueness. Hence, a two-sided matching (TSM) method considering multiple psychological behavioral behaviors and the intermediary benefit is proposed. First, a one-to-many supply-demand matching problem on online platform with multiple fuzzy preferences is described. To solve this problem, a novel weight-solving algorithm considering subjectivity and objectivity is developed. Matching utility values are determined according to the prospect theory and attribute weights. Based on desired matching numbers between logistics supply and demand agents and matching utility values, a unilateral expected matching model is constructed. Then, the expected matching matrix is obtained. By using regret theory, agent satisfaction is calculated according to the expected matching matrix. A novel formula considering risk preference coefficients is developed to calculate the intermediary benefit. Moreover, a one-to-many TSM model is established to maximize agent satisfactions of two-sided agents and the intermediary benefit. To obtain a reasonable logistics service matching scheme, a novel max-min algorithm considering fairness is developed. Finally, the rationality, effectiveness and practicality of the proposed method are verified through a one-to-many matching example on a logistics O2O platform.

关键词： Two-sided matching Logistics O2O platform Multiple psychological behavioral factors Intermediary benefit multiobjective programming

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A fuzzy programming approach to multiobjective multidimensional 0-1 knapsack problems

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FUZZY SETS AND SYSTEMS 1997年第1期86卷 1-14页

作者： Abboud, NJ Sakawa, M Inuiguchi, M HIROSHIMA UNIV FAC ENGNDEPT SYST & IND ENGNHIGASHIHIROSHIMA 739JAPAN

The objective of this paper is to present an interactive procedure for the multiobjective multidimensional 0-1 knapsack problem that takes into consideration the incorporation of fuzzy goals of the decision maker, that is easy to use since it requires from the decision maker to handle only one parameter, namely, the aspiration level of each objective, and that is fast and can treat our problem as a usual 0-1 knapsack problem using already available software, namely, the primal effective gradient method, used primarily to solve the large-scale cases. To get some statistics on the behavior of the algorithm, a number of randomly generated simulation of problems is solved. From our numerical experience, it is possible to conclude that our proposed method is a worthwhile alternative to existing methods from a practical point of view.

关键词： knapsack problem multiobjective programming fuzzy goals convex fuzzy decision

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Solid waste management system analysis by multiobjective mixed integer programming model

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 1996年第1期48卷 17-43页

作者： Chang, NB Wang, SF Department of Environmental Engineering National Cheng-Kung University Tainan Taiwan R.O.C.

The conflict between economic optimization and environmental protection has received wide attention in recent research programs for solid waste management system planning. The purpose of this analysis is to apply multiobjective mixed integer programming techniques for reasoning the potential conflict between environmental and economic goals and for evaluating sustainable strategies for waste management in a metropolitan region. The information incorporated into the optimization objectives include economic impacts, characterized by operational income and cost for waste management, air quality impacts from discharges of target pollutants due to waste incineration, noise impacts from various types of facilities operation, and traffic flow increments by garbage truck fleets. The constraint set thereby consists of mass balance, capacity limitation, operation, financial and related environmental quality constraints. Optimal strategies obtained from such an analytical scheme may provide a set of total solutions for long-term waste stream allocation, siting, resource recovery and tipping fees evaluation. The case study in the city of Kaohsiung in Taiwan is included as a demonstration. (C) 1996 Academic Press Limited

关键词： solid waste management system analysis multiobjective programming Taiwan

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MultiSQP-GS: a sequential quadratic programming algorithm via gradient sampling for nonsmooth constrained multiobjective optimization

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2024年第3期89卷 729-767页

作者： Rashidi, Mehri Soleimani-damaneh, Majid Amirkabir Univ Technol Fac Math & Comp Sci Tehran Iran Univ Tehran Coll Sci Sch Math Stat & Comp Sci Tehran Iran

In this paper, we propose a method for solving constrained nonsmooth multiobjective optimization problems which is based on a Sequential Quadratic programming (SQP) type approach and the Gradient Sampling (GS) technique. We consider the multiobjective problems with noncovex and nonsmooth objective and constraint functions. The problem functions are assumed to be locally Lipschitz. Such problems arise in important applications, many having (weak) Pareto solutions at points of nondifferentiability of the problem functions. In our algorithm, a penalty function is applied to regularize the constraints, GS is employed to overcome the subdifferential calculation burden and make the search direction computation effective in nonsmooth regions, and SQP is used for getting a local linearization. We prove the global convergence properties of our algorithm to the stationary points which approximate (weak) Pareto front. Furthermore, we illustrate the ability and efficiency of the proposed method via a MATLAB implementation on several tests problems and compare it with some existing algorithms.

关键词： multiobjective programming Nonconvex optimization Nonsmooth optimization Constrained optimization Sequential Quadratic programming (SQP) Gradient Sampling (GS) Exact penalization

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Generating the efficient set of multiobjective Integer Linear plus Linear Fractional programming Problems

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ANNALS OF OPERATIONS RESEARCH 2021年第1-2期296卷 735-753页

作者： Cherfaoui, Yasmine Moulai, Mustapha USTHB Dept Operat Res Fac Math BP 32 Algiers 16111 Algeria USTHB Fac Math LaROMaD Lab BP 32 Algiers 16111 Algeria

The problem of optimizing a linear plus linear fractional function is an important field of search, it is a difficult problem since the linear plus linear fractional function doesn't possess any convexity propriety. In this paper, we propose a method that generates the set of the efficient solutions of multiobjective integer linear plus linear fractional programming problem. Our method consists in Branch-and-Bound exploration combined with cutting plane technique that allows to remove from search inefficient solutions. The cutting plane technique takes into account the inefficiency of a solution in another problem that implies the inefficiency of that solution in our problem and uses this link to reduce the exploration's domain.

关键词： multiobjective programming Fractional programming Integer programming Branch-and-Cut

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multiobjective two-level simple recourse programming problems with discrete random variables

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OPTIMIZATION AND ENGINEERING 2021年第2期22卷 1181-1202页

作者： Yano, Hitoshi Nishizaki, Ichiro Nagoya City Univ Grad Sch Humanities & Social Sci Mizuho Ku 1 YamanohataMizuho Cho Nagoya Aichi 4678501 Japan Hiroshima Univ Grad Sch Engn 1-4-1 Kagamiyama Higashihiroshima 7398527 Japan

In this paper, we focus on multiobjective two-level simple recourse programming problems, in which multiple objective functions are involved in each level, shortages and excesses arising from the violation of the constraints with discrete random variables are penalized, and the sum of the objective function and the expectation of the amount of the penalties is minimized. To deal with such problems, a concept of Pareto Stackelberg solutions based on the reference objective levels is introduced. Using the Kuhn-Tucker approach in two-level programming, we formulate as a mixed integer programming problem, and propose an interactive algorithm to obtain a satisfactory solution of the leader from among a Pareto Stackelberg solution set based on the reference objective levels. A numerical example illustrates the proposed algorithm for a multiobjective two-level stochastic programming problem with simple recourses under the hypothetical leader.

关键词： Two-level programming Simple recourse programming multiobjective programming Pareto Stackelberg solutions

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Optimality and mixed duality in multiobjective E-convex programming

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JOURNAL OF INEQUALITIES AND APPLICATIONS 2015年第1期2015卷 1-13页

作者： Piao, Guang-Ri Jiao, Liguo Kim, Do Sang Yanbian Univ Dept Math Yanji 133002 Peoples R China Pukyong Natl Univ Dept Appl Math Busan 608737 South Korea

In this paper, we consider a class of multiobjective E-convex programming problems with inequality constraints, where the objective and constraint functions are E-convex functions which were firstly introduced by Youness (J. Optim. Theory Appl. 102: 439-450, 1999). Fritz-John and Kuhn-Tucker necessary and sufficient optimality theorems for the multiobjective E-convex programming are established under the weakened assumption of the theorems in Megahed et al. (J. Inequal. Appl. 2013: 246, 2013) and Youness (Chaos Solitons Fractals 12: 1737-1745, 2001). A mixed duality for the primal problem is formulated and weak and strong duality theorems between primal and dual problems are explored. Illustrative examples are given to explain the obtained results.

关键词： E-convex function mixed duality multiobjective programming optimality condition

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GLOBAL OPTIMIZATION ALGORITHM OF A LINEAR FRACTIONAL MULTIPLICATIVE FUNCTION OVER A PARETO-OPTIMAL SET

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2025年第5期21卷 3393-3413页

作者： Drici, Wassila Cherfaoui, Yasmine Moulai, Mustapha UMBB Dept Math Mila Algeria USTHB Fac Math LaROMaD Lab El Alia Algeria

. Integer fractional multiplicative programming problems are an important area of research that have not received much attention due to their difficulty. The fractional multiplicative function not being convex and not having in the general case the property of general convexity combined with the nonconvexity of the realizable domain, it is very difficult to find a global optimum. In this paper, we propose an algorithm that can generate an optimal solution of a multiplicative fractional linear function over the optimal Pareto set of an integer multiobjective linear fractional program.

关键词： multiobjective programming integer programming linear fractional programming quadratic programming branch and cut

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Regret analysis of sequential goal programming for multiobjective Optimal Power Flows

Regret analysis of sequential goal programming for Multiobje...

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International Power Engineering Conference (IPEC)

作者： Nangia, Uma Jain, N. K. Wadhwa, C. L. Delhi Coll Engn Dept Elect Engn Delhi India

ISBN: (纸本)9810557027

The ideal Power System Operation is achieved when various objectives like cost of generation, system transmission losses, environmental pollution etc. are simultaneously attained with minimum values. These cannot be handled by single objective techniques as the above three objectives may be conflicting in nature in certain domain. Therefore, multiobjective programming techniques have to be employed as these are capable of minimizing more than one objective simultaneously. In this paper, three objectives of multiobjective Optimal Power Flow (MOPF) problem -cost of generation, system transmission losses, environmental pollution are considered and MOPF problem is attempted sequentially using sequential Goal programming (SGP). Six strategies have been developed for IEEE 5, 14 and 30 bus systems. The optimal stategy has been identified by the Power Systems Operator using Regret Analysis.

关键词： multiobjective Optimal Power Flow multiobjective programming sequential goal programming regret analysis

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Solving a multiobjective possibilistic problem through compromise programming

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2005年第3期164卷 748-759页

作者： Parra, MA Terol, AB Gladish, BP Uría, MVR Univ Oviedo Fac Ciencias Econ & Empresariales Dpto Econ Cuantitat Oviedo Spain

Real decision problems usually consider several objectives that have parameters which are often given by the decision maker in an imprecise way. It is possible to handle these kinds of problems through multiple criteria models in terms of possibility theory. Here we propose a method for solving these kinds of models through a fuzzy compromise programming approach. To formulate a fuzzy compromise programming problem from a possibilistic multiobjective linear programming problem the fuzzy ideal solution concept is introduced. This concept is based on soft preference and indifference relationships and on canonical representation of fuzzy numbers by means of their a-cuts. The accuracy between the ideal solution and the objective values is evaluated handling the fuzzy parameters through their expected intervals and a definition of discrepancy between intervals is introduced in our analysis. (C) 2004 Elsevier B.V. All rights reserved.

关键词： multiple criteria decision making multiobjective programming compromise programming fuzzy number possibility distribution expected interval

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