Staffing a software project: A constraint satisfaction and optimization-based approach

Software development is a people intensive activity. The abilities possessed by developers are strongly related to process productivity and final product quality. Thus, one of the most important decisions to be made by a software project manager is how to properly staff the project. However, staffing software projects is not a simple task. There are many alternatives to ponder, several developer-to-activity combinations to evaluate, and the manager may have to choose a team from a larger set of available developers, according to the project and organizational needs. Therefore, to perform the staffing activity with ad hoc procedures can be very difficult and can lead the manager to choose a team that is not the best for a given situation.     

A systematic approach for product families formation in Reconfigurable Manufacturing Systems

The aim of this work is to establish a methodology for an effective working of Reconfigurable Manufacturing Systems (RMSs). These systems are the next step in manufacturing, allowing the production of any quantity of highly customised and complex products together with the benefits of mass production. In RMSs, products are grouped into families, each of which requires a system configuration. The system is configured to produce the first family of products. Once it is finished, the system is reconfigured in order to produce the second family, and so forth. Therefore, the effectiveness of a RMS depends on the formation of the best set of product families. Therefore, a methodology for grouping products into families, which takes into account the requirements of products in RMSs, is an issue of core importance. These requirements are modularity, commonality, compatibility, reusability, and product demand. The methodology starts by calculating, for each product requirement, a matrix that summarises the similarity between pairs of products. Then, through the use of the AHP methodology, a unique matrix that comprises the similarity values between products is obtained. The Average Linkage Clustering algorithm is applied to this matrix in order to obtain a dendogram that shows the diverse sets of product families that may be formed.     

Study on product quality tracing technology in supply chain

Nowadays, the product quality collaborative control technology in supply chain have been concentrated on by many researchers, however, tracing is still a less talking topic among them. Aiming to solve the quality tracing problem in supply chain, a methodology of designing information systems for traceability is proposed in this paper. Based on the former theories, the structures and models of quality tracing in supply chain are firstly introduced, also with a deep discussion on failure diagnosis technology and tracing system design, then a product quality tracing system in supply chain is established, which can provide an easier way and a new sight for the quality control in SCM (Supply Chain Management). Finally, a sample system is showed to illustrate the methodology.     

Optimal decisions for a two-echelon supply chain with capacity and demand information

Due to the applications of Internet of Things and big data in the Industry 4.0 context, more information in and out of a smart factory can be collected and shared between manufacturers and retailers. In this study, we consider two types of information that can be available in a supply chain consisting of a manufacturer and a retailer in Industry 4.0: the capacity information for the later rush production and the demand information shared between the retailer and manufacturer. In the supply chain, the manufacturer provides two orders with maximum limits by using a capacitated normal production and two capacitated rush production modes. To study the effects of the information, we investigate the optimal decisions and profits for the supply chain with and without the capacity information and demand information sharing. In addition, we propose a coordination mechanism for the supply chain with both the capacity information and demand information sharing. The coordination mechanism does not only rely on cost parameters, but also on the capacity and demand information. The numerical examples show that the supply chain profit can be improved by as large as 16.76% in the coordinated system, compared with the original system without the capacity information and demand information sharing.     

A supply chain disruption recovery strategy considering product change under COVID-19

A recent global outbreak of Corona Virus Disease 2019 (COVID-19) has led to massive supply chain disruption, resulting in difficulties for manufacturers on recovering their supply chains in a short term. This paper presents a supply chain disruption recovery strategy with the motivation of changing the original product type to cope with that. In order to maximize the total profit from product changes, a mixed integer linear programming (MILP) model is developed with combining emergency procurement on the supply side and product changes by the manufacturer as well as backorder price compensation on the demand side. The model uses a heuristic algorithm based on ILOG CPLEX toolbox. Experimental results show that the proposed disruption recovery strategy can effectively reduce the profit loss of manufacturer due to late delivery and order cancellation. It is observed that the impact of supply chain disruptions is reduced. The proposed model can offer a potentially useful tool to help the manufacturers decide on the optimal recovery strategy whenever the supply chain system experiences a sudden massive disruption.     

CONSAT: A parallel constraint satisfaction system

In this paper we describe the parallelization of a medium-size symbolic fixed-point computation, CONSAT. CONSAT is a constraint satisfaction system that computes globally consistent solutions. The parallel version of CONSAT is implemented using abstractions from a parallel programming toolbox we developed. The toolbox is intended for novice parallel programmers, and programs based on abstractions from this toolbox may be executed on both uniprocessors and shared-memory multiprocessors without modifications. We explain how parallelism is introduced, and how concurrent accesses to shared data structures are handled. We will also describe the performance of CONSAT on sample inputs.     

Agent-based negotiation and decision making for dynamic supply chain formation

Modern businesses are facing the challenge of effectively coordinating their supply chains from upstream to downstream services. It is a complex problem to search, schedule, and coordinate a set of services from a large number of service resources under various constraints and uncertainties. Existing approaches to this problem have relied on complete information regarding service requirements and resources, without adequately addressing the dynamics and uncertainties of the environments. The real-world situations are complicated as a result of ambiguity in the requirements of the services, the uncertainty of solutions from service providers, and the interdependencies among the services to be composed. This paper investigates the complexity of supply chain formation and proposes an agent-mediated coordination approach. Each agent works as a broker for each service type, dedicated to selecting solutions for each service as well as interacting with other agents in refining the decision making to achieve compatibility among the solutions. The coordination among agents concerns decision making at strategic, tactical, and operational level. At the strategic level, agents communicate and negotiate for supply chain formation; at the tactical level, argumentation is used by agents to communicate and understand the preferences and constraints of each other; at the operational level, different strategies are used for selecting the preferences. Based on this approach, a prototype has been implemented with simulated experiments highlighting the effectiveness of the approach.     

SCOlog: A logic-based approach to analysing supply chain operation dynamics

In a complex business world, characterised by globalisation and rapid rhythms of change, understanding supply chain (SC) operation dynamics is crucial. This paper describes a logic-based approach to analysing SC operation dynamics, named SCOlog. SC operation is modelled in a declarative fashion and it is simulated following rule-based execution semantics. This approach facilitates the automated explanation of simulated SC operational behaviours and performance. The automated explanation support provided by SCOlog is found to improve the understanding of the domain for non-SCM experts. Furthermore, SCOlog allows for maintainability and reusability.     

An agent-based approach for e-manufacturing and supply chain integration

A major problem facing manufacturing organisations is how to provide efficient and cost-effective responses to the unpredictable changes taking place in a global market. This problem is made difficult by the complexity of supply chain networks coupled with the complexity of individual manufacturing systems within supply chains. Current systems such as manufacturing execution systems (MES), supply chain management (SCM) systems and enterprise resource planning (ERP) systems do not provide adequate facilities for addressing this problem. This paper presents an approach that would enable manufacturing organisations to dynamically and cost-effectively integrate, optimise, configure, simulate, restructure and control not only their own manufacturing systems but also their supply networks, in a co-ordinated manner to cope with the dynamic changes occurring in a global market. This is realised by a synergy of two emerging manufacturing concepts: Agent-based agile manufacturing systems and e-manufacturing. The concept is to represent a complex manufacturing system and its supply network with an agent-based modelling and simulation architecture and to dynamically generate alternative scenarios with respect to planning, scheduling, configuration and restructure of both the manufacturing system and its supply network based on the coordinated interactions amongst agents.     

Coordinating a three-level supply chain with delay in payments and a discounted interest rate

Both researchers and practitioners recognize the importance of the interactions between financial and inventory decisions in the development of cost effective supply chains. Moreover, achieving effective coordination among the supply chain players has become a pertinent research issue. This paper considers a three-level supply chain, consisting of a capital-constrained supplier, a retailer, and a financial intermediary (bank), coordinating their decisions to minimize the total supply chain costs. Specifically, we consider a retailer managing its cash through the supplier’s bank, in return for permissible delay in payments from the supplier. The bank, benefiting from increasing its cash holdings with the retailer’s cash deposits, offers the supplier a discount on its borrowing rate. We show that the proposed coordination mechanism achieves significant cost reduction, by up to 26.2%, when compared to the non-coordinated model. We also find that, with coordination, the retailer orders in larger quantities than its economic order quantity, and that a higher return on cash for the retailer leads to a higher order quantity. Furthermore, we empirically validate our proposed coordination mechanism, by showing that banks, retailers, and suppliers have much to gain through collaboration. Thus, using COMPUSTAT datasets for the years 1950 through 2012, we determine the most important factors that affect the behavior of the retailers and suppliers in granting and receiving trade credit. Our results indicate that engaging into such a coordination mechanism is a win–win situation to all parties involved.     

A fuzzy constraint satisfaction approach for electronic shopping assistance

The Internet and World Wide Web offer an additional channel for consumers to find, select, and buy products. However, unlike shopping in the traditional store, consumers have no direct contact with human clerks to get the required information in the electronic store. The objective of this paper is to propose a fuzzy constraint satisfaction approach to help buyers find fully satisfactory or replacement products in electronic shopping. For the buyer who can give precise product requirements, the proposed approach can generate product-ranking lists based on the satisfaction degrees of each product to the given requirements. For the buyer who may not input accurate requirements, a similarity analysis approach is proposed to assess buyer requirements automatically during his browsing process. The proposed approach could help buyers find the preferred products on the top of the ranking list without further searching the remaining pages. The experimental results show the applicability of the proposed approach for electronic shopping assistance.     

An agent-based framework for collaborative negotiation in the global manufacturing supply chain network

This paper applies the multi-agent system paradigm to collaborative negotiation in a global manufacturing supply chain network. Multi-agent computational environments are suitable for dealing with a broad class of coordination and negotiation issues involving multiple autonomous or semiautonomous problem solving agents. An agent-based multi-contract negotiation system is proposed for global manufacturing supply chain coordination. Also reported is a case study of mobile phone global manufacturing supply chain management.     

Supporting decisions in real-time enterprises: autonomic supply chain systems

Supporting decisions in real time has been the subject of a number of research efforts. This paper reviews the technology and architecture necessary to create an autonomic supply chain for a real-time enterprise for supply chain systems. The technologies weaved together include knowledge-based event managers, intelligent agents, radio frequency identification (RFID), database and system integration, and enterprise resource planning systems. This article is part of the “Handbook on Decision Support Systems” edited by Frada Burstein and Clyde W. Holsapple (2008) Springer.     

A system dynamics framework for integrated reverse supply chain with three way recovery and product exchange policy

With the technological advancements and rapid changes in demand pattern, diverse ranges of products are entering into the market with reduced lifecycle which leads to the environmental disasters. The awareness of product take-back and recovery has been increasing in various supply chains not only due to the obligation imposed by legislation but also competitive economics worldwide. In this paper, we develop a system dynamics framework for a closed-loop supply chain network with product exchange and three way recovery policy, namely; product remanufacturing, component reuse and remanufacturing, and raw material recovery. In the simulation study, we investigate the significance of various factors including product exchange, collection and remanufacturing; their interactions and the type of their impact on bullwhip and profitability through sensitivity and statistical analysis. Our results suggest that the inclusion of three way recovery in reverse channel and product exchange policy in the forward channel reduce the order variation and bullwhip effect at both retailer and distributor level and increases the profitability of RL operations. In addition, we redefine the reverse logistics framework with “open-loop” in which the remanufactured products are redistributed only in the secondary market and compare the performance of open-loop model with that of closed-loop. Extended numerical investigation provides insights to the decision makers regarding the actions which can lead to better performance of the system.     

Generating customized yet factually consistent information: a constraint satisfaction approach

We present an information customization framework that leverages a hybrid of adaptive hypermedia and intelligent techniques, in particular constraint satisfaction methods, to generate customized and factually consistent information based on a user profile. Information customization is modeled as a constraint satisfaction problem, whereby a solution is derived by (a) satisfying user-model constraints to select a user-specific set of ‘information snippets’; and (b) establishing inter-snippet consistency to ensure that all snippets are compatible with each other. Our approach takes the unique step of establishing factually consistency – via the satisfaction of inter-snippet constraints – between heterogeneous information snippets. A customized information package is generated by systematically synthesizing the set of user-specific and factually consistent information snippets. The featured information customization framework incorporates variations of various search and constraint satisfaction methods. The work is applied in an E-Healthcare setting leading to the generation of customized healthcare information.     

A systematic approach for coupling user satisfaction with product design

A fundamental assumption in this paper is that user satisfaction depends on product design. The approach consists of 5 steps: (1) define user satisfaction, (2) decompose product design elements, (3) conduct experiments, (4) develop relationship models, and (5) analyse critical design features. In order to demonstrate the practicability of this approach, relationship models were developed based on experimental data using a total of 60 subjects (30 American and 30 Korean subjects). In addition, critical design features and their common properties were identified for audio/visual consumer products. Similarities and differences between American and Korean consumers were discussed. The resulting relationship models can be used to predict user satisfaction and provide significant remedies for design change.     

Network optimization in supply chain: A KBGA approach

In this paper, we present a Knowledge Based Genetic Algorithm (KBGA) for the network optimization of Supply Chain (SC). The proposed algorithm integrates the knowledge base for generating the initial population, selecting the individuals for reproduction and reproducing new individuals. From the literature, it has been seen that simple genetic-algorithm-based heuristics for this problem lead to and large number of generations. This paper extends the simple genetic algorithm (SGA) and proposes a new methodology to handle a complex variety of variables in a typical SC problem. To achieve this aim, three new genetic operators—knowledge based: initialization, selection, crossover, and mutation are introduced. The methodology developed here helps to improve the performance of classical GA by obtaining the results in fewer generations. To show the efficacy of the algorithm, KBGA also tested on the numerical example which is taken from the literature. It has also been tested on more complex problems.     

A systematic approach for supply chain improvement using design structure matrix

Supply chain is a complex system that involves many system elements from various functional areas. Performance of a supply chain heavily depends on the effectiveness of communication and coordination among these system elements and functional areas. However, a large and complex supply chain usually makes it difficult to coordinate and thus degrades its performance. This paper focuses on the development of a systematic approach with the following objectives: (1) to identify and quantify the interactions among the system elements in a supply chain; (2) to decompose the large interdependent group of system elements into smaller and manageable sub-groups; and thus (3) to improve the structure of the supply chain system. A supply chain system is first decomposed into subsystems and system elements from which the interactions (i.e., independent, dependent and interdependent relationships) are studied and documented by design structure matrix (DSM). Next, the interaction strengths among the related system elements are quantified. Cluster analysis is used to decompose the large interdependent group into smaller ones in order to provide a better supply chain system structure. The effectiveness of this systematic approach is demonstrated by an illustrative example. The result shows that it is able to improve the system structure of a supply chain that will be useful for the supply chain reengineering.     

A decision rule for coordination of inventory and transportation in a two-stage supply chain with alternative supply sources

This paper deals with a two-stage supply chain that consists of two distribution centers and two retailers. Each member of the supply chain uses a (Q,R) inventory policy, and incurs standard inventory holding and backlog costs, as well as ordering and transportation costs. The distribution centers replenish their inventory from an outside supplier, and the retailers replenish inventory from one of the two distribution centers. When a retailer is ready to replenish its inventory that retailer must decide whether it should replenish from the first or second distribution center. We develop a decision rule that minimizes the total expected cost associated with all outstanding orders at the time of order placement; the retailers then repeatedly use this decision rule as a heuristic. A simulation study which compares the proposed policy to three traditional ordering policies illustrates how the proposed policy performs under different conditions. The numerical analysis shows that, over a large set of scenarios, the proposed policy outperforms the other three policies on average.     

Coordinating orders in a two echelon supply chain with controllable lead time and ordering cost using the credit period

In this research, a coordination mechanism based on a credit period in a two echelon supply chain with one buyer and one supplier, is designed. The buyer is faced with uncertain demand by coping with normal distribution. Both lead time and ordering cost for receiving his order can be reduced at an added cost; in other words, they are controllable. The optimization models with and without integration are proposed. Then a way to coordinate orders in supply chain based on the credit period so that the total cost of supply chain would be minimized is designed. By using this mechanism we also discuss how the credit period is to be determined in order to achieve channel coordination and a win-win outcome. Finally, numerical examples are solved to illustrate the theoretical results and obtain the managerial insights.