Improving the efficiency of the purchasing process using total cost of ownership information : The case of heating electrodes at Cockerill Sambre S.A.

Improving the efficiency of the purchasing process provides important opportunities to increase a firm's profitability. In this paper we introduce a mathematical programming model that uses total cost of ownership information to simultaneously select suppliers and determine order quantities over a multi-period time horizon. The total cost of ownership quantifies all costs associated with the purchasing process and is based on the activities and cost drivers determined by an activity based costing system. Our approach is motivated by the purchasing problem of heating electrodes at Cockerill Sambre S.A. a Belgian multinational steel producer. In this case quality issues account for more than 70 % of the total cost of ownership making the quality of a supplier a critical success factor in the vendor selection process.Efficiency; Heating; Processes; Purchasing;

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;

Stochastic make-to-stock inventory deployment problem: an endosymbiotic psychoclonal algorithm based approach

Integrated steel manufacturers (ISMs) have no specific product, they just produce finished product from the ore. This enhances the uncertainty prevailing in the ISM regarding the nature of the finished product and significant demand by customers. At present low cost mini-mills are giving firm competition to ISMs in terms of cost, and this has compelled the ISM industry to target customers who want exotic products and faster reliable deliveries. To meet this objective, ISMs are exploring the option of satisfying part of their demand by converting strategically placed products, this helps in increasing the variability of product produced by the ISM in a short lead time. In this paper the authors have proposed a new hybrid evolutionary algorithm named endosymbiotic-psychoclonal (ESPC) to decide what and how much to stock as a semi-product in inventory. In the proposed theory, the ability of previously proposed psychoclonal algorithms to exploit the search space has been increased by making antibodies and antigen more co-operative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results compared with other evolutionary algorithms such as genetic algorithms (GA) and simulated annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained and convergence time required to reach the optimal/near optimal value of the solution

An ESPC algorithm based approach to solve inventory deployment problem

Global competitiveness has enforced the hefty industries to become more customized. To compete in the market they are targeting the customers who want exotic products, and faster and reliable deliveries. Industries are exploring the option of satisfying a portion of their demand by converting strategically placed products, this helps in increasing the variability of product produced by them in short lead time. In this paper, authors have proposed a new hybrid evolutionary algorithm named Endosymbiotic-Psychoclonal (ESPC) algorithm to determine the amount and type of product to stock as a semi product in inventory. In the proposed work the ability of previously proposed Psychoclonal algorithm to exploit the search space has been increased by making antibodies and antigen more cooperative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results obtained, are compared with other evolutionary algorithms such as Genetic Algorithm (GA) and Simulated Annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained, and convergence time required to reach the optimal /near optimal value of the solution

Sustainable diets in the UK—developing a systematic framework to assess the environmental Impact, cost and nutritional quality of household food purchases

Sustainable diets should not only respect the environment but also be healthy and affordable. However, there has been little work to assess whether real diets can encompass all three aspects. The aim of this study was to develop a framework to quantify actual diet records for health, affordability and environmental sustainability and apply this to UK food purchase survey data. We applied a Life Cycle Assessment (LCA) approach to detailed food composition data where purchased food items were disaggregated into their components with traceable environmental impact data. This novel approach is an improvement to earlier studies in which sustainability assessments were based on a limited number of “food groups”, with a potentially high variation of actual food items within each group. Living Costs and Food Survey data for 2012, 2013 and 2014 were mapped into published figures for greenhouse gas emissions (GHGE, taking into account processing, transport and cooking) and land use, a diet quality index (DQI) based on dietary guidelines and food cost, all standardised per household member. Households were classified as having a ‘more sustainable’ diet based on GHGE, cost and land use being less than the median and DQI being higher than the median. Only 16.6% of households could be described as more sustainable; this rose to 22% for those in the lowest income quintile. Increasing the DQI criteria to >80% resulted in only 100 households being selected, representing 0.8% of the sample. The framework enabled identification of more sustainable households, providing evidence of how we can move toward better diets in terms of the environment, health, and costs

Tanzania Country Climate Risk Profile Series, Kilolo District

The agricultural sector in Tanzania has been exposed to high climatic risks for the past several decades (Arce & Caballero, 2015). Experts and farmers assert that climatic risks including unpredictable rainfall, prolonged drought, and increased incidences of pests and diseases have resulted in declining agricultural productivity. Concomitantly, the rivers, streams, soils, and forests from which the rural poor build their livelihoods are on the verge of depletion. The situation has been further exacerbated by unstable commodity prices. Future climatic projections show that the climate trends are likely to worsen in the coming years. For instance, mean annual temperatures in Tanzania are predicted to increase by up to 2.7°C by 2060, and by close to 50% by 2090 (Irish Aid, 2018). Similarly, day and night temperatures are also expected to increase. Rainfall will become increasingly erratic both locally and regionally, with both floods and droughts growing in intensity and frequency. Smallholder farmers have the poorest access to resources such as land tenure, water resources, crop and livestock insurance, financial capital, and markets, and thus are the least risk-resilient. Women farmers in particular suffer systematic discrimination in terms of access to these resources. Women are also culturally expected to execute the most laborious agricultural tasks in addition to their household responsibilities of caregiving, preparing meals, and collecting fuel and water. Meanwhile, men tend to be responsible for tasks involving financial exchange, such as land acquisition, sourcing capital for production, purchasing and applying chemicals, and identifying buyers. This cultural norm is reinforced by the tenure system, which assigns land ownership almost exclusively to men. These factors make women the most vulnerable sub-group of smallholder farmers (Irish Aid, 2018). The national government, donor community, private sector, and development partners have invested in helping households prepare for such climate scenarios. A number of policies, strategies, programmes, and guidelines have been documented with the goal of boosting the adaptation capacity of vulnerable groups. Prominent among these are the National Agricultural Policy (NAP 2013), the National Climate Change Strategy (NCCS 2012), the National Adaptation Programme of Action (NAPA 2007), and the Climate-Smart Agriculture implementation guideline. Despite these efforts, several issues remain unaddressed due to a lack of coordination among relevant actors. The development of a local Climate-Smart Agriculture Profile can support the clarification of roles and crucial points of coordination to assist in this effort. This Kilolo District profile thus underscores the climate-smart agriculture (CSA) investments undertaken by farming households in the region. This profile is an output of the CSA/SuPER project on Upscaling CSA with small scale food producers, organized via the Village Saving and Lending Association (VSLA) Project, and implemented by Cooperative Assistance and Relief Everywhere (CARE International), the International Center for Tropical Agriculture (CIAT) (now part of the Alliance of Bioversity International and CIAT), Sokoine University of Agriculture, and Wageningen University and Research. Both qualitative and quantitative methods were used to gather the information herein, in accordance with the methodology employed by Mwongera et al. (2015). Secondary information was collected through an extensive literature review. Primary information was collected from interviews with agricultural experts, farmer focus group discussions, stakeholder workshops, and farmer interviews in Kilolo District. This profile is organized into six major sections based on the analytical steps of the study. The first section describes the contextual importance of agriculture to Kilolo livelihoods and households. The second describes historic and future climatic trends. The third section highlights farmers’ priority value chains. The fourth section addresses the challenges and cross-cutting issues in the sector. The fifth section details climate hazards experienced by farmers, as well as the current and proposed adaptation strategies. Finally, the sixth section outlines the policies related to CSA and the institutions that facilitate implementation of climate change initiatives

Modeling Electoral Coordination: Parties and Legislative Lists in Uruguay

During each electoral period, the strategic interaction between voters and political elites determines the number of viable candidates in a district. In this paper, we implement a hierarchical seemingly unrelated regression model to explain electoral coordination at the district level in Uruguay as a function of district magnitude, previous electoral outcomes and electoral regime. Elections in this country are particularly useful to test for institutional effects on the coordination process due to the large variations in district magnitude, to the simultaneity of presidential and legislative races held under different rules, and to the reforms implemented during the period under consideration. We find that district magnitude and electoral history heuristics have substantial effects on the number of competing and voted-for parties and lists. Our modeling approach uncovers important interaction-effects between the demand and supply side of the political market that were often overlooked in previous research

Climate change, agriculture and Fairtrade: identifying the challenges and opportunities

This paper presents the findings of a study commissioned by the UK's Fairtrade Foundation on the implications of climate change for agricultural producers in Fairtrade value chains