Multiple Objective Integer Programming Research Articles

Re-designing industrial products on a multi-objective basis: a case study

Environmentally conscious product design has received significant attention recently. Apart from new products’ development, environmental considerations may also apply for products that manufacturers have already launched in the market. In this case, manufacturers can also make use of their considerable experience gained over the phases following product design (eg production, use, end-of-life, etc) in order to promote substantial improvements as regards their re-designed products’ performance. This paper presents a methodological framework for manufacturers based on Multiple Objective Integer Programming in order to re-design industrial products. The proposed approach includes re-designed product's cost, environmental impact, weight and ease of disassembly. The methodology is applied to a real-world case study, that of netMod network terminal.

Presenting an algorithm of integer nonlinear multiple objective programming in conditions of uncertainty for balanced scorecard method (case study in Islamic Azad University, Semnan Branch)

A B S T R A C T Balanced scorecard is a performance appraisal method planned for measuring the organizational efficiency to develop their strategies. Organization's strategies in a specified period are the main inputs in this model. Furthermore, due to nature, experts' opinions play the vital role in determining the strategies. In this research, the proposed algorithm is designed by using fuzzy set covering problem and non-linear multiple objective integer programming (zero and one variables), so that it can be useful to choose the best combination of strategies for specified period of time with the least deviation in expertsopinions. The presented model is carried out in Islamic Azad University, Semnan Branch. The results indicate that the designed model can provide the best combination of strategies for entering into the balanced scorecard system.

A discussion of scalarization techniques for multiple objective integer programming

In this paper we consider solution methods for multiobjective integer programming (MOIP) problems based on scalarization. We define the MOIP, discuss some common scalarizations, and provide a general formulation that encompasses most scalarizations that have been applied in the MOIP context as special cases. We show that these methods suffer some drawbacks by either only being able to find supported efficient solutions or introducing constraints that can make the computational effort to solve the scalarization prohibitive. We show that Lagrangian duality applied to the general scalarization does not remedy the situation. We also introduce a new scalarization technique, the method of elastic constraints, which is shown to be able to find all efficient solutions and overcome the computational burden of the scalarizations that use constraints on objective values. Finally, we present some results from an application in airline crew scheduling as evidence.

A Combined MOIP–MCDA Approach to Building and Screening Atmospheric Pollution Control Strategies in Urban Regions

This article presents a methodological approach for the formulation of control strategies capable of reducing atmospheric pollution at the standards set by European legislation. The approach was implemented in the greater area of Thessaloniki and was part of a project aiming at the compliance with air quality standards in five major cities in Greece. The methodological approach comprises two stages: in the first stage, the availability of several measures contributing to a certain extent to reducing atmospheric pollution indicates a combinatorial problem and favors the use of Integer Programming. More specifically, Multiple Objective Integer Programming is used in order to generate alternative efficient combinations of the available policy measures on the basis of two conflicting objectives: public expenditure minimization and social acceptance maximization. In the second stage, these combinations of control measures (i.e., the control strategies) are then comparatively evaluated with respect to a wider set of criteria, using tools from Multiple Criteria Decision Analysis, namely, the well-known PROMETHEE method. The whole procedure is based on the active involvement of local and central authorities in order to incorporate their concerns and preferences, as well as to secure the adoption and implementation of the resulting solution.

A multiple objective integer programming approach for planning franchise expansion

The number and configuration of franchise outlets in a market defines the distribution strategy of a franchise company. The introduction of new franchise outlets contributes to conflict between the franchisee and franchisor over the degree of market penetration. The selection of sites for new franchises is an important factor in the long-term profitability of many types of franchises. This selection process requires consideration of objectives of the franchisee and franchisor which are often conflicting in nature. This paper deals with the problem of locating new franchises in an existing franchise network using multiple objective integer programming models and methods.

An Application of the AXIS Solution Framework to Multiple Objective Aggregate Production Planning

This paper provides data on the first application of a prototype of the AXIS solution framework. AXIS (algorithms combined with knowledge systems in an interactive sequence) is a framework for interactively combining structured algorithms that seek a best solution with knowledge-based expert systems that seek expert heuristic solutions. This paper tests the framework using an interactive multiple objective integer programming algorithm combined with heuristics taken from the domain of aggregate production planning. The results indicate the AXIS framework can be successful in generating high quality solutions, in vastly reduced solution times compared to the structured algorithms, at much lower costs compared to the expert heuristics working alone.

Media selection via multiple objective integer programming

Multiple Objective Integer Linear Programming (MOILP) is presented as an aid to media selection. A MOILP analysis approach recognizes the lack of infinite division in media choices and provides the decisionmaker with an efficient set of alternatives. The decisionmaker may then utilize non-quantifiable criteria to make the final media selection or may use the efficient set developed by the MOILP procedure as a screening mechanism. These screened solutions would then be submitted to further analysis to consider interaction effects, non-linearity and so on. The approach is outlined and an illustrative example using somewhat standard data is provided.