Goal programming

About: Goal programming is a research topic. Over the lifetime, 4330 publications have been published within this topic receiving 117758 citations.

Multiobjective differential evolution algorithm based on decomposition for a type of multiobjective bilevel programming problems

Abstract: This paper considers the multiobjective bilevel programming problem (MOBLPP) with multiple objective functions at the upper level and a single objective function at the lower level. By adopting the Karush-Kuhn-Tucker (KKT) optimality conditions to the lower level optimization, the original multiobjective bilevel problem can be transformed into a multiobjective single-level optimization problem involving the complementarity constraints. In order to handle the complementarity constraints, an existing smoothing technique for mathematical programs with equilibrium constraints is applied. Thus, a multiobjective single-level nonlinear programming problem is formalized. For solving this multiobjective single-level optimization problem, the scalarization approaches based on weighted sum approach and Tchebycheff approach are used respectively, and a constrained multiobjective differential evolution algorithm based on decomposition is presented. Some illustrative numerical examples including linear and nonlinear versions of MOBLPPs with multiple objectives at the upper level are tested to show the effectiveness of the proposed approach. Besides, NSGA-II is utilized to solve this multiobjective single-level optimization model. The comparative results among weighted sum approach, Tchebycheff approach, and NSGA-II are provided.

Combining Goal Programming Model With Simulation Analysis For Bank Asset Liability Management

Abstract: The aim of this paper is to present an Asset Liability Management (ALM) technique, which combines a goal programming model with a simulation analysis to determine the balance sheet of a bank for the year 2000. To attain this goal, we analyzed the 1999 balance sheet of a Greek commercial bank facing conflicting goals such as returns, liquidity, solvency, and expansion of deposits and loans under uncertainty. An optimizer was embedded in a simulation model to obtain different optimal solutions for a set of interest rate scenarios, while a sensitivity analysis explored the effects of alterations in the order of goal priorities.

A Comprehensive Dea Approach for the Resource Allocation Problem based on Scale Economies Classification

Abstract: This paper is concerned with the resource allocation problem based on data envelopment analysis (DEA) which is generally found in practice such as in public services and in production process. In management context, the resource allocation has to achieve the effective-efficient-equality aim and tries to balance the different desires of two management layers: central manager and each sector. In mathematical programming context, to solve the resource allocation asks for introducing many optimization techniques such as multiple-objective programming and goal programming. We construct an algorithm framework by using comprehensive DEA tools including CCR, BCC models, inverse DEA model, the most compromising common weights analysis model, and extra resource allocation algorithm. Returns to scale characteristic is put major place for analyzing DMUs’ scale economies and used to select DMU candidates before resource allocation. By combining extra resource allocation algorithm with scale economies target, we propose a resource allocation solution, which can achieve the effective-efficient-equality target and also provide information for future resource allocation. Many numerical examples are discussed in this paper, which also verify our work.

Goal Programming and Financial Planning Models for Highway Rehabilitation

Abstract: This paper examines the problem of capital budgeting in the area of highway maintenance. Emphasis is placed on specific, real-world user concerns relating to standard capital budgeting models, and suggestions are made for improving planning in this area. A two-phase approach to capital budgeting is suggested as a mechanism for resolving some of these concerns. In phase 1 a financial planning model is used as a means of determining appropriate budget levels. In phase 2 a goal programming model for achieving desired levels of service is given. A brief description is given of such a two-phase system currently being implemented in a Canadian transport ministry.