A mathematical programming approach for supplier selection using Activity Based Costing.

Vendor selection is an important problem in today's competitive environment . Decisions involve the selection of vendors and the determination of order quantities to be placed with the selected vendors. In this research we develop a mathematical programming model for this purpose using an Activity Based Costing approach. The system computes the total cost of ownership, thereby increasing the objectivity in the selection process and giving the opportunity for different kinds of sensitivity analysis. Moreover, it allow the analyst to objectively evaluate alternative purchasing policies due to the underlying analytic and rigorous decision model.Activity based costing; Mathematical programming; Selection;

Optimising economic, environmental, and social objectives: a goal-programming approach in the food sector

The business-decision environment is increasingly complicated by the emergence of competing economic, environmental, and social goals, a notion typified by the current pressures of global economic instability and climate-change targets. Trade-offs are often unclear and contributions by different actors and stakeholders in the supply chain may be unequal but, due to the interdependencies between businesses and stakeholders in relation to total environmental or social impact, a whole chain, simultaneous, and strategic approach is required. After a review of relevant literature and the identification of knowledge gaps, the author introduces and illustrates the use of goal programming as a technique that could facilitate this approach and uses real case evidence for alternative food supply chain strategies, at local, regional, and national levels. It is shown that the method can simplify a complex simultaneous decision situation into a useful and constructive decision and planning framework. Results show how a priori beliefs may be challenged and how operational and resource efficiency could be improved through the use of such a model, which enables a broad stakeholder appreciation and the opportunity to explore and test new environmental or social challenges

Water Supply Planning under Interdependence of Actions: Theory and Application

An ongoing water supply planning problem in the Regional Municipality of Waterloo, Ontario, Canada, is studied to select the best water supply combination, within a multiple-objective framework, when actions are interdependent. The interdependencies in the problem are described and shown to be essential features. The problem is formulated as a multiple-criteria integer program with interdependent actions. Because of the large number of potential actions and the nonconvexity of the decision space, it is quite difficult to find nondominated subsets of actions. Instead, a modified goal programming technique is suggested to identify promising subsets. The appropriateness of this technique is explained, and the lessons learned in applying it to the Waterloo water supply planning problem are described

Assessing farmer behaviour as affected by policy and technological innovations: bio-economic farm models

Farm Management,

Integrating multicriteria decision analysis and scenario planning : review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of "metacriteria" (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country

Robust Multi-Objective Sustainable Reverse Supply Chain Planning: An Application in the Steel Industry

In the design of the supply chain, the use of the returned products and their recycling in the production and consumption network is called reverse logistics. The proposed model aims to optimize the flow of materials in the supply chain network (SCN), and determine the amount and location of facilities and the planning of transportation in conditions of demand uncertainty. Thus, maximizing the total profit of operation, minimizing adverse environmental effects, and maximizing customer and supplier service levels have been considered as the main objectives. Accordingly, finding symmetry (balance) among the profit of operation, the environmental effects and customer and supplier service levels is considered in this research. To deal with the uncertainty of the model, scenario-based robust planning is employed alongside a meta-heuristic algorithm (NSGA-II) to solve the model with actual data from a case study of the steel industry in Iran. The results obtained from the model, solving and validating, compared with actual data indicated that the model could optimize the objectives seamlessly and determine the amount and location of the necessary facilities for the steel industry more appropriately.This article belongs to the Special Issue Uncertain Multi-Criteria Optimization Problem