Organizations have to allocate resources, time, and workforce in many projects at the same time. Selection and scheduling of the projects have a significant impact on effective project management. However, most of the...
详细信息
Organizations have to allocate resources, time, and workforce in many projects at the same time. Selection and scheduling of the projects have a significant impact on effective project management. However, most of the studies in the literature do not solve the selection and scheduling problems simultaneously. This study aims to design an interactive process to integrate selection and scheduling processes in the project management. For this purpose, a new multi objectiveprogramming model is proposed. The project scores are presented as belief de-grees (i.e., distributions to linguistic term levels) that are gathered as a result of the weighted cumulative belief degree approach. By the use of the belief degrees, projects could be selected and scheduled based on the satis-faction level of the problem owner. The proposed model considers conditions and restrictions in management of business development projects such as the progress percentage of the projects in a period, the complementary and mutual exclusive relations between projects, etc. An interactive solution procedure is developed in order to solve the proposed model. The proposed model and the solution procedure are applied in an information technology company for their business development projects
An alternative optimization technique via multiobjectiveprogramming for constrained optimization problems with interval-valued objectives has been proposed. Reduction of interval objective functions to those of nonin...
详细信息
An alternative optimization technique via multiobjectiveprogramming for constrained optimization problems with interval-valued objectives has been proposed. Reduction of interval objective functions to those of noninterval (crisp) one is the main ingredient of the proposed technique. At first, the significance of interval-valued objective functions along with the meaning of interval-valued solutions of the proposed problem has been explained graphically. Generally, the proposed problems have infinitely many compromise solutions. The objective is to obtain one of such solutions with higher accuracy and lower computational effort. Adequate number of numerical examples has been solved in support of this technique.
A multi-objective stochastic programming model is developed for supply chain design under uncertainty using an interactive approach. This is a comprehensive model, which includes both the strategic and tactical levels...
详细信息
A multi-objective stochastic programming model is developed for supply chain design under uncertainty using an interactive approach. This is a comprehensive model, which includes both the strategic and tactical levels. The uncertainty regarding demands, supplies, processing and transportation costs is captured by generating discrete scenarios with given probabilities of occurrences. The objective functions involved are the expected total cost (min), the variance of the total costs (min) to get a robust design, and the probability of not meeting a certain budget (min). Then, an interactive multi-objective technique with explicit trade-off information given named surrogate worth trade-off (SWT) method is used to solve the multi-objective model.
In this paper, we model multi-class multi-stage assembly systems with finite capacity as queueing networks. It is assumed that different classes (types) of products are produced by the production system and products&#...
详细信息
In this paper, we model multi-class multi-stage assembly systems with finite capacity as queueing networks. It is assumed that different classes (types) of products are produced by the production system and products' orders for different classes are received according to independent Poisson processes. Each service station of the queueing network specifies a manufacturing or assembly operation, in that processing times for different types of products are independent and exponentially distributed random variables with service rates, which are controllable, and the queueing discipline is First Come First Served (FCFS). Different types of products may be different in their routing sequences of manufacturing and assembly operations. For modeling multi-class multi-stage assembly systems, we first consider every class separately and convert the queueing network of each class into an appropriate stochastic network. Then, by using the concept of continuous-time Markov processes, a system of differential equations is created to obtain the distribution function of manufacturing lead time for any type of product, which is actually the time between receiving the order and the delivery of finished product. Furthermore, we develop a multi-objective model with three conflicting objectives to optimally control the service rates, and use goal attainment method to solve a discrete-time approximation of the original multi-objective continuous-time problem. (C) 2013 Elsevier Ltd. All rights reserved.
This paper presents a general-purpose software framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO. A concise overview of evolutionary algori...
详细信息
This paper presents a general-purpose software framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO. A concise overview of evolutionary algorithms for multiobjective optimization is given. A substantial number of methods has been proposed so far, and an attempt of conceptually unifying existing approaches is presented here. Based on a fine-grained decomposition and following the main issues of fitness assignment, diversity preservation and elitism, a conceptual model is proposed and is validated by regarding a number of state-of-the-art algorithms as simple variants of the same structure. This model is then incorporated into the ParadisEO-MOEO software framework. This framework has proven its validity and high flexibility by enabling the resolution of many academic, real-world and hard multiobjective optimization problems. (C) 2010 Elsevier B.V. All rights reserved.
The location of undesirable facilities involves economic, environmental and social impacts. The costs associated and the rejection of facilities by nearby population are crucial concerns. This paper introduces a Multi...
详细信息
The location of undesirable facilities involves economic, environmental and social impacts. The costs associated and the rejection of facilities by nearby population are crucial concerns. This paper introduces a Multiobjective Mixed-Integer Linear programming (MMILP) approach to identify locations and capacities of biogas plants to treat animal waste from dairy farms, and assign each farm to a subset of the opened biogas plants. Three objectives were considered in the mathematical model: minimizing initial investment, operation and maintenance costs;minimizing transportation cost;and minimizing social rejection. The proposed model was applied to the Entre-Douro-e-Minho Region in Portugal. The approach provided as output a set of Pareto optimal solutions, represented by maps using a Geographic Information System, each one achieving a unique combination of economic and social performance. (C) 2017 Elsevier Ltd. All rights reserved.
The widespread use of the Internet has significantly changed the behavior of homebuyers. Using online real estate agents, homebuyers can rapidly find some modern houses that meet their needs;however, most current onli...
详细信息
The widespread use of the Internet has significantly changed the behavior of homebuyers. Using online real estate agents, homebuyers can rapidly find some modern houses that meet their needs;however, most current online housing systems provide limit features. In particular, existing systems fail to consider homebuyers' housing goals and risk attitudes. To increase effectiveness, online real estate agents should provide an efficient matching mechanism, personalized service and house ranking with the aim of increasing both buyers' satisfaction and deal rate. An efficient online real estate agent should provide an easy way for homebuyers to find (rank) a suitable house (alternatives) with consideration of their different housing philosophies and risk attitudes. In order to comprehend these ambiguous housing goals and risk attitudes, it is also indispensable to determine a satisfaction level for each fuzzy goal and constraint. In this study, we propose fuzzy goal programming with an S-shaped utility function as a decision aid to help homebuyers in choosing their preferred house via the Internet in an easy way. With the use of a decision aid, homebuyers can specify their housing goals and constraints with different priority levels and thresholds as a matching mechanism for a fuzzy search, while the matching mechanism can be translated into a standard query language for a regular relational database. Moreover, a laboratory experiment is conducted on a real case to demonstrate the effectiveness of the proposed approach. The results indicate that the proposed method provides better customer satisfaction than manual systems in housing selection service. (C) 2014 Elsevier B.V. All rights reserved.
In this article, a new framework for evolutionary algorithms for approximating the efficient set of a multiobjective optimization (MOO) problem with continuous variables is presented. The algorithm is based on populat...
详细信息
In this article, a new framework for evolutionary algorithms for approximating the efficient set of a multiobjective optimization (MOO) problem with continuous variables is presented. The algorithm is based on populations of variable size and exploits new elite preserving rules for selecting alternatives generated by mutation and recombination. Together with additional assumptions on the considered MOO problem and further specifications on the algorithm, theoretical results on the approximation quality such as convergence in probability and almost sure convergence are derived. (c) 2005 Elsevier B.V. All rights reserved.
Renewable liquid fuels produced from biomass, hydrogen, and carbon dioxide play an important role in reaching climate neutrality in the transportation sector. For large-scale deployment, production facilities and corr...
详细信息
Renewable liquid fuels produced from biomass, hydrogen, and carbon dioxide play an important role in reaching climate neutrality in the transportation sector. For large-scale deployment, production facilities and corresponding logistics have to be established. However, the implementation of such a large-scale renewable fuel production network requires acceptance by citizens. To gain insights into the structure of efficient and socially accepted renewable fuel production networks, we propose a bi-objective mixed -integer programming model. In addition to an economic objective function, we consider social acceptance as a second objective function. We use results from a conjoint analysis study on the acceptance and preference of renewable fuel production networks, considering the regional topography, facility size, production pathway, and raw material transportation to model social acceptance. We find significant trade-offs between the economic and social acceptance objective. The most favorable solution from a social acceptance perspective is almost twice as expensive as the most efficient economical solution. However, it is possible to strongly increase acceptance at a moderate expense by carefully selecting sites with preferred regional topography.
In the present study, a modified variant of Differential Evolution (DE) algorithm for solving multi-objective optimization problems is presented. The proposed algorithm, named Multi-objective Differential Evolution Al...
详细信息
In the present study, a modified variant of Differential Evolution (DE) algorithm for solving multi-objective optimization problems is presented. The proposed algorithm, named Multi-objective Differential Evolution Algorithm (MODEA) utilizes the advantages of Opposition-Based Learning for generating an initial population of potential candidates and the concept of random localization in mutation step. Finally, it introduces a new selection mechanism for generating a well distributed Pareto optimal front. The performance of proposed algorithm is investigated on a set of nine bi-objective and five tri-objective benchmark test functions and the results are compared with some recently modified versions of DE for MOPs and some other Multi objective Evolutionary Algorithms (MOEA5). The empirical analysis of the numerical results shows the efficiency of the proposed algorithm. (C) 2011 Elsevier B.V. All rights reserved.
暂无评论