A hybrid genetic algorithm model for transshipment management decisions

This chapter describes a Genetic Algorithm (GA) based Fuzzy Goal Programming (FGP) model to solve a Multiobjective Bilevel Programming Problem (MOBLPP) with a set of chance constraints within a structure of decentralized decision problems. To formulate the model, the chance constraints are converted first to their crisp equivalents to employ FGP methodology. Then, the tolerance membership functions associated with fuzzily described goals of the objective functions are defined to measure the degree of satisfaction of Decision Makers (DMs) with achievement of objective function values and also to obtain the degree of optimality of vector of decision variables controlled by upper-level DM in the decision system. In decision-making process, a GA scheme is adopted to solve the problem and thereby to obtain a proper solution for balancing execution powers of DMs in uncertain environment. A numerical example is provided to illustrate the method.

As a subfield of artificial intelligence, genetic algorithm (GA) was introduced in the 1970s to tackle various types (both continuous and discrete) of combinatorial decision problems facing many business enterprises. These problems include routine but complex managerial challenges associated with supply chain activities of sourcing, making, selling, and delivering goods and services. With the emergence of supply chain principles in today's business world, GA has increased its role in improving managerial decision-making processes and subsequently enhancing supply chain efficiency by avoiding the sub-optimisation of problem solutions. Despite its application potentials, we have seen the limited use of GA for supply chain management. To make the best use of GA for supply chain management, this paper introduces the theoretical underpinning of GA and then explains how effectively it works for solving difficult supply chain problems. In so doing, this paper reviews the past record of success in GA applications to supply chain fields and then identifies the most promising areas of supply chain management in which to apply GA.

Fuzzy goal programming for health-care organization

Multiple-criteria decision-making in two-sided assembly line balancing: A goal programming and a fuzzy goal programming models

Social Media Networks (SMNs) are collaborative tools used in an increasing rate in many business and industrial environments. These are often used in parallel with dedicated Collaborative Technologies (CTs) which are specifically designed to handle dedicated tasks. Within this research project the specific area of supply chain management is the focus of investigation. Two case studies where CTs are already extensively employed have been conducted to evaluate the scope of SMN usage and to confirm the particular benefits provided and to identify limitations. The overall purpose being to provide guidelines on joint CT/SMN deployment in developing supply chains. The application of SMNs to supply chain operations is fundamental to addressing the emerging need for increased P2P (peer-to-peer) type communication. This type of communication is between individuals and is typified by increased relationship type interaction. This is in contrast to traditional B2B (business-to-business) communication which is typically conducted on a transactional basis especially where it is confined by the characteristics of dedicated CTs. SMNs can be applied in supply chain networks to deal with unexpected circumstances or problem solving, capture market demands and customer feedback, and in general provide a medium to react to unplanned events. Crucially, they provide a platform where the issues can be addressed on a P2P basis in the absence of confrontational, transactional type interactions. The case studies reported in this paper concern EU based companies, one being a major national aluminium profile extruder, the second being a bottling plant for a global soft drinks manufacturer. In both cases the application of CTs to their supply chains is well established. However whilst both companies could readily identify the strengths of their CT systems (information and data sharing, data storage and retrieval) they could also identify limitations. These limitations included the lack of real time interaction at a P2P level and, interestingly, the lack of a common language used between different CT systems in B2B communication. Overall, the comments of the case study companies was that the SMN provided valuable adjuncts to existing CT systems, but that the SMNs were not integrated with the CT systems. There was a strongly perceived need for a better understanding of the contrasting and complementary capabilities of CTs and SMNs so that in future fully integrated systems could be implemented. Future work in this area will focus on the development of guidelines and procedures for achieving such complementarity in international collaborative supply chains.

Defined as the fulfillment of nutritional requirements of people working at different places such as schools, hospitals etc., public food service’s one of the most important stage is menu planning. Menu planning is such a complex process that one should take not only many factors into consideration like cost, energy/nutrition units, taste, diversity etc., but also some aims which should be practiced simultaneously. One of the programs which can be used in programming for such a process is goal programming, a technic for multi-purpose decisions. In the goal programming as a data based technic, fuzzy goal programming models have also been advanced for the situations in which data are not certain. In this study, an example lunch meal menu planning is prepared for the workers between 19 and 30 years old. The menu is planned as non-optional. During the process of planning, fuzzy goal programming method was used in consequence of fuzziness in data.

Fuzzy goal programming has important applications in many areas of supply chain, logistics, transportation and shipping business. Business management has complications, and there exist many interactions between the factors of its components. The locomotive of world trade is maritime transport and approximately 90% of the products in the world are transported by sea. Optimization of maritime operations is a challenge in order to provide technical, operational and financial benefits. Fuzzy goal programming models attract interests of many scholars, therefore the objective of this paper is to investigate the problem of minimization of total cost and minimization of loss or damage of containers returned from destination port. There are various types of fuzzy goal programming problems based on models and solution methods. This paper employs fuzzy goal programming with triangular fuzzy numbers, membership functions, constraints, assumptions as well as the variables and parameters for optimizing the solution of the model problem. The proposed model presents the mathematical algorithm, and reveals the optimal solution according to satisfaction rank from 0 to 1. Providing a theoretical background, this study offers novel ideas to researchers, decision makers and authorities.

This study has tried to evaluate the impact of integrating cloud-based solutions in e-commerce logistics. An explanatory research design was followed for this purpose and both secondary qualitative and quantitative information was obtained from existing academic journals and case studies. The findings indicated the important role of cloud-based solutions in the areas of supply chain management, delivery efficiency and customer satisfaction. The findings also revealed that integrating cloud-based logistics solutions allows DHL Express, Amazon, Walmart and other companies in their e-commerce services. In addition, it allows both e-commerce businesses and logistic providers to share real-world data, which ensures constant data flow in their supply chain. Besides, completely relying on secondary data is the main limitation of this study as it is the main risk of collecting biased data.

p-Median problem is one of the most applicable problem in the areas of supply chain management and operation research. There are various versions of these problems. Continuous p-median is one of them where the facility points and the demand points lie in an ’n’ dimensional hyperspace. It has been proved that this problem is NP-complete and most of the algorithms that have been defined are mere approximations. In this paper, we present a meta-heuristic based approach that calculates the median points given a set of demand points with arbitrary demands. The algorithm is a combination of genetic algorithms, particle swarm optimization and a number of novel techniques that aims to further improve the result. The algorithm is tested on known data sets as and we show’s its performance in comparison to other known algorithms applied on the same problem.

Optimization of transportation and distribution costs is one of the important issues in the supply chain management area. It is caused by their large contribution to the logistics costs that can reach up to 40%. Thus, choosing the right route is one of the efforts that can be done to resolve the issue. This study aims to optimize the capacitated vehicle routing problem with time windows (CVRPTW) for mineral water company distributor with pick-up and delivery problem. To achieve the aim, this study used hybrid algorithm, Genetic Algorithm (GA) and Tabu Search Algorithm (TS). The selection of this hybrid algorithm is due to its capability in minimizing travel distance. The result of this study shows that not only the algorithm has successfully reduced the existing route but also predicted the optimum number of homogenous fleet. By running the algorithm, this study concludes that the number of the optimum routes for this study can be reduced for up to 15.99% than the existing route.

Efficient supply chain management is crucial for survival and success in a turbulent world. Current economic crisis increases its importance even further. This conceptual paper reviews latest findings in the most relevant areas of supply chain management. The objective of this paper is to identify global supply chain management challenges and its solutions. In order to achieve the objectives, a thorough literature review was conducted; main findings are reviewed. This review has covered Indian industry, HaiHa’s supplier, and other global perspectives. Therefore, the challenges might be different according to the origin countries and industries. Besides, it is also found that the challenges can be mitigated with some alternatives derived from reviewing the case studies. The findings shown that in order to compete with global participation, efforts on seeking out the solutions would be much encouraged and embedded into the organizations.

Supply chain challenges require not only effective management, but also a new innovative strategy to reduce costs and maximize its efficiency. Traditional problem-solving methodologies specific to the areas of supply chain management (SCM) find their limits when confronted with an inventive problem or a problem containing a contradiction. TRIZ (theory of inventive problem solving) is an effective theory for systematizing innovation and solving complex problems containing contradictions. Thus, the use of the theory TRIZ can be considered as a way to meet future challenges in SCM fields and get innovative solutions. This paper presents a method for solving supply chain problems and achieving a low-cost, based on complementarities between TRIZ and discrete event simulation and specific methods for solving supply chain problems. In the proposed model, a witness simulation model of the initial problem is developed to optimize the problem and find the system limits. Then, specific problem solving methods are applied to change the original description of problem and move towards a space in which a solution can be found. The discrete event simulation allows for experiments on the system to be created and analyzed. Thus, an experimental design was developed to establish the cause-and-effect relationships between the parameters of the system in order to formulate a generalized system of contradictions. And finally, ARIZ 85C, the most mature meta-methods of TRIZ, is used to address related contradictions for searching for an innovative solution, which must be subsequently implemented and evaluated in the discrete event simulation. The suitability of this new approach is finally proven through an industrial case study conducted in a company specialized in the manufacture of electronic devices for automobiles.

The study explores the transformative role of blockchain technology in enhancing transparency and traceability within the agricultural food supply chain. By leveraging blockchain's inherent characteristics of decentralization, immutability, and security, stakeholders can significantly improve information sharing and visibility from farm to consumer. The study delves into how blockchain addresses longstanding transparency and traceability issues that have plagued the agricultural sector. Real-world examples illustrate blockchain's successful application in agriculture, showcasing its capacity to boost transparency, operational efficiency, and trust among supply chain participants. These case studies demonstrate how blockchain creates tamper-proof records, enhances end-to-end visibility, and provides reliable, real time data. The technology's potential to combat fraud, promote sustainability, and ensure product authenticity is also explored. Furthermore, the research investigates blockchain's impact on food safety, particularly when integrated with Internet of Things (IoT) devices and smart contracts. These synergies enable automated, secure data collection and the execution of predefined agreements, further streamlining supply chain processes. Successful implementations across various areas of supply chain management, including logistics, inventory tracking, and quality control, are highlighted to demonstrate the practical benefits of blockchain adoption. By providing an in-depth analysis of blockchain's potential, this study underscores its pivotal role in building consumer trust regarding food safety, quality, and origin. The research concludes by discussing the challenges and opportunities for widespread blockchain adoption in agriculture, offering insights into its future trajectory and potential to revolutionize the global food supply chain.

Background: Within highly complex supply chain networks, driven by the trend of digitalization, supply chain relationship management becomes one of the central enablers in increasing supply chain performance. While the influences of globalization and digitalization on the supply chains are increasing, the power allocation within several markets is centralized to a small number of companies. The objective of this paper is to investigate the research gap concerning the impact of power asymmetries on the supply chain, in addition to the trend of digitalization. Methods: A literature review on power, in the research area of supply chain management and logistics, is used to synthesize the current state of the art in this research field and to provide a comprehensive definition of the concept of power. Conclusions: While this paper provides an overview of the impact of power allocations, according to supply chain digitalization and in the present research of supply chain management, it also develops a definition of Power in Supply Chain Management in general. Linked to this definition, this research elaborates on the research gap between power allocations and the digitalization of the supply chain.

English language fluency among graduates is becoming an important capability that graduates need for employment. The industry has noted the declining level of English among Malaysian graduates thus strategies and policies need to be implemented. This paper gives an overview on three areas of literature that is pertinent to this topic: competencies and future employment, language learning strategies and supplier learning. This paper suggest that a model for capability development from the area of supply chain management could be extrapolated as a framework for future research on analyzing the strategies that graduates employ on their own to improve their capability of English language fluency.