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

A supplier selection using a hybrid grey based hierarchical clustering and artificial bee colony

Selection of one or a combination of the most suitable potential providers and outsourcing problem is the most important strategies in logistics and supply chain management. In this paper, selection of an optimal combination of suppliers in inventory and supply chain management are studied and analyzed via multiple attribute decision making approach, data mining and evolutionary optimization algorithms. For supplier selection in supply chain, hierarchical clustering according to the studied indexes first clusters suppliers. Then, according to its cluster, each supplier is evaluated through Grey Relational Analysis. Then the combination of suppliers’ Pareto optimal rank and costs are obtained using Artificial Bee Colony meta-heuristic algorithm. A case study is conducted for a better description of a new algorithm to select a multiple source of suppliers

Applying total cost of ownership for strategic procurement : three industrial case studies.

In this paper we elaborate on a Total Cost of Ownership supplier selection methodology that we have constructed using three real life case studies which are presented in this article. Analysing the value chain of the firm, data on the costs generated by the purchasing policy and on supplier performance are collected using Activity Based Costing (ABC). Since a spreadsheet cannot encompass all these costs, let alone optimise the supplier selection and inventory management policy, a mathematical programming model is used. Possible savings of between 6 and 14% are obtained for the three cases.Case studies; Studies;

Wood-based construction project supplier selection under uncertain starting date

There is a growing interest in supply management systems in today's competitive business environment. Importance of implementing supply management systems especially in home construction industry is due to the fact that several risks arising from different sources can adversely affect the project financially or its timely completion. Some risks of construction projects are out of managers' control while other risks such as supply related ones can usually be controlled and directed by effective managerial tactics. In this paper, we address the supplier selection problem (SSP) in wood-based construction industry (housing projects) in the presence of project commencement uncertainties. Based on the suppliers' (vendors') reaction towards these uncertainties in the delivery time, we explore two cases: (a) supplier selection with buyer penalty for a delay (SSPD) where the price of product increases with the delay; (b) supplier selection with quantity reduction for a buyer delay (SSQRD). Three heuristic-based supplier selection approaches are proposed and tested on randomly generated data sets. The proposed approaches show promising result

Optimizing strategic sourcing in the healthcare supply chain with consideration of physician preference and vendor scorecards

This research focuses on the design of a procurement model for expensive medical supplies in a healthcare supply chain. A deterministic optimization model generates recommendations for optimal purchases of products in a given planning period. The model combines common concepts of supply chain procurement such as leveraging tiered pricing, ensuring supply base diversity with phenomena unique to healthcare supply chain such as consideration of physician preference for products. The deterministic optimization model minimizes total spend over a chosen planning period with consideration of four key decision parameters: Physician preference requirements (which are imposed as rules on product substitutability), Upper limits on vendor market share to ensure a suitably diverse supply base Vendors’ performance scores to impose standards for product pricing, quality, service, etc. Quantity discount rebate parameters for bulk purchasing to help contain medical costs The optimization model reveals the extent to which higher product substitutability and lower supply base diversity may help hospitals reduce total procurement costs. Experiments with the optimization model also reveal the potential consequences of rater biases in vendor scorecards on procurement cost. The various parameter combinations listed above may be used in negotiating contracts for better pricing. In summary, this research addresses questions pertinent to healthcare supply chains concerning the possible cost of physician preference for products, the impact of subjective scorecards on procurement costs, the effect of planning period on procurement plans, and the cost of vendor diversity

The Optimal Employment of Supply Chain management Decision Support Agents: an Exploratory Study

The issue of interest here is the employment of decision support agents in supply chain management. The study discusses the sorts of supply-related managerial tasks that decision support agents have been assigned, and how well or poorly they have performed these tasks. This research suggests the reasons why organizations might elect to invest supply chain management responsibilities in decision support agents rather than human functionaries. Finally, this research concludes by presenting a best fit construct for optimal decision making opportunities

Coupling Performance Measurement and Collective Activity: The Semiotic Function of Management Systems. A Case Study

Theories about management instruments often enter dualistic debates between structure and agency: do instruments determine the forms of collective activity (CA), or do actors shape instruments to their requirements, or are instruments and concrete activity decoupled, as some trends of new institutionalist theory assume? Attempts to overcome the dualistic opposition between structure and activity stem from diverse sources: actors’ networks theory, structuration theory, pragmatism, theory of activity, semiotics. Performance measurement and management systems can be defined as structural instruments engaged in CA. As such they constrain the activity, but they do not determine it. Reciprocally, they are modified by the way CA uses them and makes sense of them. The central thesis of this paper will be that it is impossible to study the role of performance measurement as a common language in organizations independently from the design of the CA in which it is engaged. There is a not deterministic coupling between structure (i.e. management technical tools) and CA (i.e. business processes). The transformation of CA entails a transformation in the meaning of the “performance” concept, in the type of measurement required and in the performance management practices. The relationship between performance measurement and CA is studied here in the production division of a large electricity utility in France. The research extended over several years and took place when two new management systems were simultaneously implemented: a new management accounting system and an integrated management information system (ERP), both in the purchasing process. The new management accounting system was designed by the purchasing department; the new management information system was designed by the operational departments. Whereas the coherence between both projects could have been given by their common subordination to the rebuilding of CA (the purchasing process), their disconnection from concrete CA opened the possibility of serious dissonances between them. Both the new performance management system and the new ERP met difficulties to provide common languages, since the dimension of CA was taken for granted and consequently partly ignored in the engineering of both systems. When CA incurs radical transformations, actors’direct discursive exchanges about it, “collective activity about collective activity”, become necessary to ensure a flexible and not deterministic coupling between CA and new management systems. This reflexive and collective analysis of the process by actors themselves requires the establishment of “communities of process”, which can jointly redesign the CA and its performance measurement system. We conclude that performance measurement can be a common language as far as there is a clear and shared understanding of how CA should concretely take place and should be assigned to the different categories of actors.Business Process; Collective Activity; Community of Process; Management Instruments; Performance Measurement; Semiotics; Theory of Activity

A hierarchical approach to multi-project planning under uncertainty

We survey several viewpoints on the management of the planning complexity of multi-project organisations under uncertainty. A positioning framework is proposed to distinguish between different types of project-driven organisations, which is meant to aid project management in the choice between the various existing planning approaches. We discuss the current state of the art of hierarchical planning approaches both for traditional manufacturing and for project environments. We introduce a generic hierarchical project planning and control framework that serves to position planning methods for multi-project planning under uncertainty. We discuss multiple techniques for dealing with the uncertainty inherent to the different hierarchical stages in a multi-project organisation. In the last part of this paper we discuss two cases from practice and we relate these practical cases to the positioning framework that is put forward in the paper