Multi-choice goal programming with utility functions

Topology design of remote patient monitoring system concerning qualitative and quantitative issues

Revised multi-choice goal programming

As consumer needs for product features change rapidly, companies must develop new products (NPD) that satisfy these needs in the shortest possible time. Consumer product selection behavior is generally overlooked when developing new products. This is a more complicated problem for consumers belonging to multiple types, such as hospitals and patients. Quality function deployment (QFD) is a good and commonly used method for product design and selection. Choosing the right product design for a company is a crucial strategic consideration to satisfy the needs of consumers and the company’s technical requirements. Designing a new product is multicriteria decision‐making (MCDM). In this study, the analytical hierarchy process (AHP), QFD, and multichoice goal programming (MCGP) were combined to address the design and selection of new products. This integrated method considers both tangible (qualitative) and intangible (quantitative) factors, as well as “the higher criterion is better” and “the lower criteria is better” when selecting new design projects. To prove the practicality and sustainable value of the model, we considered a Taiwanese company that developed medical aid products as an example. This paper suggests a good decision‐making tool for selecting a new product design based on “more is better/less is better” criteria.

An integrated approach to catering supplier selection using AHP-ARAS-MCGP methodology

Interval-valued intuitionistic fuzzy numbers (IVIFNs) characterized by a membership function and a non-membership function with values that are intervals, have strong ability to handle imprecise and ambiguous information in real-world applications.This paper proposes an integrated maximizing consistency and multi-choice goal programming (MCGP) approach to handle hybrid multi-criteria group decision making problems based on IVIFNs.Firstly, the hybrid decision information (including crisp numbers, intervals, intuitionistic fuzzy numbers and linguistic variables) are normalized into the IVIFNs.Then, an ordinal consistency index and a cardinal consistency index are proposed to measure the consistency between the individual opinion and the group opinion, respectively.And an optimal model based on maximizing consistency is constructed to derive the weights of experts.Afterwards, the comprehensive ratings and the ranking values of alternatives are obtained by the hybrid weighted aggregation operator and the proposed ratio function of IVIFNs, respectively.Furthermore, a MCGP model based on the ranking values is constructed to identify the optimal alternatives and their optimum quantities.At length, an illustrative case is provided to verify the proposed approach.

The allocation of construction land is an important task in land-use planning. Whether implementation of planning decisions is a success or not, usually depends on a reasonable and scientific distribution method. Considering the constitution of land-use planning system and planning process in China, multiple levels and multiple objective decision problems is its essence. Also, planning quantity decomposition is a two-level system optimization problem and an optimal resource allocation decision problem between a decision-maker in the topper and a number of parallel decision-makers in the lower. According the characteristics of the decision-making process of two-level decision-making system, this paper develops an optimal allocation model of construction land based on two-level linear planning. In order to verify the rationality and the validity of our model, Baoan district of Shenzhen City has been taken as a test case. Under the assistance of the allocation model, construction land is allocated to ten townships of Baoan district. The result obtained from our model is compared to that of traditional method, and results show that our model is reasonable and usable. In the end, the paper points out the shortcomings of the model and further research directions.

A web-based Decision Support System WebOptim for solving multiple objective optimization problems is presented. The system WebOptim is designed in a modular principle, extensively using XML as communication standard and web services. Its basic characteristics are: user-independent, multisolver-admissibility, method-independent, heterogeneity, web-accessibility. Core system module is an original generalized interactive scalarizing method. It incorporates a number of thirteen interactive methods. Most of the known scalarizing approaches (reference point approach, reference direction approach, classification approach etc.) are realized in this method. The Decision Maker (DM) can choose the most suitable for him/her form for setting his/her preferences: objective weights, aspiration levels, aspiration directions, aspiration intervals. This information could be changed interactively by the DM during the solution process. Depending on the DM's preferences form the suitable scalarizing method is chosen automatically. The chapter begins with an overview of Decision Support Systems (DSS). Examples of DSSs and their applications are discussed.

The integration of economic and social objectives is essential for Islamic bank to stimulate economic growth through the effective management and allocation of wealth and resources. This article proposes a hybrid mathematical optimization between the analytic hierarchy process (AHP) and multi-choice goal programming (MCGP) methods. The hybrid methods make the amalgamation of economic and social objectives possible in the multi-objective model of Islamic banking. The AHP method is used to determine the priorities or weights on each of the economic and social objectives. MCGP on the other hand, serves as an optimizer to the Multi-objective Decision Making (MODM) model that fits the priorities to the objectives and possible target goals. Results confirmed on the practicality and flexibility of the hybrid AHP-MCGP model which enable Islamic banks to better utilize their financial resources based on the priorities and multiple target goals. The feasible achievement of multi-objective with an interval target goal has offered the avenue for the decision makers at Islamic bank to satisfy economic and social goals simultaneously.

This paper explores the study of multi-choice multi-objective transportation problem (MCMTP) under the environment of utility function approach. MCMTP is converted to multi-objective transportation problems (MOTP) by transforming the multi-choice parameters like cost, demand, and supply to real-valued parameters. A general transformation procedure using binary variables is illustrated to reduce MCMTP into MOTP. Most of the MOTP are solved by goal programming (GP) approach. Using GP, the solution of MOTP may not be satisfied all the time by the decision maker (DM) when the proposed problem contains interval-valued aspiration level. To overcome this difficulty, here we propose the approaches of revised multi-choice goal programming (RMCGP) and utility function into the MOTP and then compared the solution between them. Finally, numerical examples are presented to show the feasibility and usefulness of our paper.

Optimizing sustainable and renewable energy portfolios using a fuzzy interval goal programming approach

A hybrid genetic algorithm for integrating virtual cellular manufacturing with supply chain management considering new product development

A robust bi-objective mathematical model for disaster rescue units allocation and scheduling with learning effect

Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Production planning is one of the most important issues of managers in industry. Production managers face up with several goals that sometimes conflict with each other. Operations research techniques with considering the constraints, optimize organizational goals. Objectives of all these techniques are raising productivity in the organization. In this paper, the researchers present a multi-objective linear fractional model of production planning in wood and metal company. One of the difficulties in solving the multiple objective fractional problems is computational problem that arises from of variability, in the example of Charnes and Cooper (1961) methods. In this research, fuzzy approach issued to solve multiple objective fractional mathematical problems of Khavar-E-Miane Wood and Metal Company. First, with some assumptions, the fuzzy linear fractional goal programming method of Pal has been used to solve the problem of production planning. Then, the fuzzy method of Dutta is utilized to solve the problem. Comparison of results showed that both methods have identical solution. Key words: Production planning, fuzzy goal programming, productivity, fuzzy fractional programming, wood and metal company.

With the widespread use of the Internet, adopting e-learning systems in courses has gradually become more and more important in universities in Taiwan. However, because of limitations of teachers' time, selecting suitable online IT tools has become very important. This study proposes an analytic hierarchy process (AHP)–multi-choice goal programming (MCGP) evaluation model as a decision aid to help decision makers obtain appropriate online IT tools considering the time limitations of teachers and students. To demonstrate the usefulness of the proposed method, this study implements the evaluation model in computer courses at a university in central Taiwan. For different purposes, teachers can set different time limitations and aspiration levels for each goal to rank the range of possible IT tools. With the AHP–MCGP evaluation model, teachers can find the most suitable time for the allocation of possible IT tools in the e-learning system to improve students' learning practice.