A fuzzy multi-objective covering-based vehicle location model for emergency services

Timeliness is one of the most important objectives that reflect the quality of emergency services such as ambulance and firefighting systems. To provide timeliness, system administrators may increase the number of service vehicles available. Unfortunately, increasing the number of vehicles is generally impossible due to capital constraints. In such a case, the efficient deployment of emergency service vehicles becomes a crucial issue. In this paper, a multi-objective covering-based emergency vehicle location model is proposed. The objectives considered in the model are maximization of the population covered by one vehicle, maximization of the population with backup coverage and increasing the service level by minimizing the total travel distance from locations at a distance bigger than a prespecified distance standard for all zones. Model applications with different solution approaches such as lexicographic linear programming and fuzzy goal programming (FGP) are provided through numerical illustrations to demonstrate the applicability of the model. Numerical results indicate that the model generates satisfactory solutions at an acceptable achievement level of desired goals.     

A genetic algorithm approach for multi-objective optimization of supply chain networks

Supply chain network (SCN) design is to provide an optimal platform for efficient and effective supply chain management. It is an important and strategic operations management problem in supply chain management, and usually involves multiple and conflicting objectives such as cost, service level, resource utilization, etc. This paper proposes a new solution procedure based on genetic algorithms to find the set of Pareto-optimal solutions for multi-objective SCN design problem. To deal with multi-objective and enable the decision maker for evaluating a greater number of alternative solutions, two different weight approaches are implemented in the proposed solution procedure. An experimental study using actual data from a company, which is a producer of plastic products in Turkey, is carried out into two stages. While the effects of weight approaches on the performance of proposed solution procedure are investigated in the first stage, the proposed solution procedure and simulated annealing are compared according to quality of Pareto-optimal solutions in the second stage.     

Two-echelon, multi-commodity supply chain network design with mode selection, lead-times and inventory costs

Designing distribution networks - as one of the most important strategic issues in supply chain management - has become the focus of research attention in recent years. This paper deals with a two-echelon supply chain network design problem in deterministic, single-period, multi-commodity contexts. The problem involves both strategic and tactical levels of supply chain planning including locating and sizing manufacturing plants and distribution warehouses, assigning the retailers' demands to the warehouses, and the warehouses to the plants, as well as selecting transportation modes.We have formulated the problem as a mixed integer programming model, which integrates the above mentioned decisions and intends to minimize total costs of the network including transportation, lead-times, and inventory holding costs for products, as well as opening and operating costs for facilities. Moreover, we have developed an efficient Lagrangian based heuristic solution algorithm for solving the real-sized problems in reasonable computational time.     

Dynamic Location and Entry Mode Selection of Multinational Manufacturing Facilities under Uncertainty: A Chance-constrained Goal Programming Approach

As the global marketplace continues to expand, the firm's location strategy should shift from domestic to international. An international location problem is different from the traditional domestic location problem in that the former is influenced by a greater variety of uncontrollable, unpredictable, and dynamic factors than is the latter. These factors may include political conditions, expropriation risks, trade regulations, currency exchange rates, cultural differences, and global distribution channel structures. Consequently, the international location problem is more diverse, volatile and complex. Nevertheless, a vast majority of the location literature overlooked many important international aspects. To help the multinational firm formulate viable location strategies in the changing world marketplace, this paper proposes multiple-period, multiple-plant, multiple-objective, and stochastic location model.     

Fuzzy heterogeneous multiattribute decision making method for outsourcing provider selection

One of the critical activities for outsourcing success is outsourcing provider selection, which may be regarded as a type of fuzzy heterogeneous multiattribute decision making (MADM) problems with fuzzy truth degrees and incomplete weight information. The aim of this paper is to develop a new fuzzy linear programming method for solving such MADM problems. In this method, the decision maker’s preferences are given through pair-wise alternatives’ comparisons with fuzzy truth degrees, which are expressed with trapezoidal fuzzy numbers (TrFNs). Real numbers, intervals, and TrFNs are used to express heterogeneous decision information. Giving the fuzzy positive and negative ideal solutions, we define TrFN-type fuzzy consistency and inconsistency indices based on the concept of the relative closeness degrees. The attribute weights are estimated through constructing a new fuzzy linear programming model, which is solved by using the developed fuzzy linear programming method with TrFNs. The relative closeness degrees of alternatives can be calculated to generate their ranking order. An example of the IT outsourcing provider selection problem is analyzed to demonstrate the implementation process and applicability of the method proposed in this paper.     

Modeling supplier selection and the use of option contracts for global supply chain design

As supply chains become more and more dependent on the efficient movement of materials among facilities that are geographically dispersed there is more opportunity for disruption. One of the common disruptions is the loss of production capability at supplier sites. We formulate a two-stage stochastic program and a solution procedure to optimize supplier selection to hedge against these disruptions. This model allows for the effective quantitative exploration of the trade-off between cost and risks to support improved decision-making in global supply chain design. A realistic case study is explored.     

Fuzzy-genetic approach to aggregate production-distribution planning in supply chain management

Aggregate production-distribution planning (APDP) is one of the most important activities in supply chain management (SCM). When solving the problem of APDP, we are usually faced with uncertain market demands and capacities in production environment, imprecise process times, and other factors introducing inherent uncertainty to the solution. Using deterministic and stochastic models in such conditions may not lead to fully satisfactory results. Using fuzzy models allows us to remove this drawback. It also facilitates the inclusion of expert knowledge. However, the majority of existing fuzzy models deal only with separate aggregate production planning without taking into account the interrelated nature of production and distribution systems. This limited approach often leads to inadequate results. An integration of the two interconnected processes within a single production-distribution model would allow better planning and management. Due to the need for a joint general strategic plan for production and distribution and vague planning data, in this paper we develop a fuzzy integrated multi-period and multi-product production and distribution model in supply chain. The model is formulated in terms of fuzzy programming and the solution is provided by genetic optimization (genetic algorithm). The use of the interactive aggregate production-distribution planning procedure developed on the basis of the proposed fuzzy integrated model with fuzzy objective function and soft constraints allows sound trade-off between the maximization of profit and fillrate. The experimental results demonstrate high efficiency of the proposed method.     

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

Two-sided assembly lines are especially used at the assembly of large-sized products, such as trucks and buses. In this type of a production line, both sides of the line are used in parallel. In practice, it may be necessary to optimize more than one conflicting objectives simultaneously to obtain effective and realistic solutions. This paper presents a mathematical model, a pre-emptive goal programming model for precise goals and a fuzzy goal programming model for imprecise goals for two-sided assembly line balancing. The mathematical model minimizes the number of mated-stations as the primary objective and it minimizes the number of stations as a secondary objective for a given cycle time. The zoning constraints are also considered in this model, and a set of test problems taken from literature is solved. The proposed goal programming models are the first multiple-criteria decision-making approaches for two-sided assembly line balancing problem with multiple objectives. The number of mated-stations, cycle time and the number of tasks assigned per station are considered as goals. An example problem is solved and a computational study is conducted to illustrate the flexibility and the efficiency of the proposed goal programming models. Based on the decision maker's preferences, the proposed models are capable of improving the value of goals.     

Supply chain modeling in uncertain environment with bi-objective approach

Supply chain is viewed as a large-scale system that consists of production and inventory units, organized in a serial structure. Uncertainty is the main attribute in managing the supply chains. Managing a supply chain (SC) is very difficult, since various sources of uncertainty and complex interrelationships among various entities exist in the SC. Uncertainty may result from customer’s demand variability or unreliability in external suppliers. In this paper we develop an inventory model for an assembly supply chain network (each unit has at most one immediate successor, but any number of immediate predecessors) which fuzzy demand for single product in one hand and fuzzy reliability of external suppliers in other hand affect on determination of inventory policy in SCM. External supplier’s reliability has determined using a fuzzy expert system. Also the performance of supply chain is assessed by two criteria including total cost and fill rate. To solve this bi-criteria model, hybridization of multi-objective particle swarm optimization and simulation optimization is considered. Results indicate the efficiency of proposed approach in performance measurement.     

Developing Oregon’s renewable energy portfolio using fuzzy goal programming model

Renewable energy continues to be a hot topic in the United States affecting security and sustainability. A model to create renewable energy portfolio is established using guidelines drawn by Oregon’s Renewable Portfolio Standard (RPS) legislation with the objective of responding to a 25% of the state electricity demand by renewable resources in 2025. The fuzzy goal programming model is adaptable to accommodate changes in energy costs and future advances in technology maturity. It can also take into consideration the preferences of policy-makers and stakeholders. This model can help to reveal the costs and benefits of complex decisions regarding renewable energy.     

多目标规划的LINDO求解方法

按多目标优先级逐级展开,将多目标转化为线性规划,再利用LinDo求解,从而使多目标规划的求解变得简单易行。     

Modelling a vendor–Telco supply network to deliver two types of telephony services

In this paper, we examine a telecom vendor selling Advanced Intelligent Network (AIN) software applications and service-creation-tools to a telephone company (Telco) who then deploy these products on it's network to provide AIN services and queries. The supply of AIN software applications and tools by the vendor to the Telco who then uses them to create AIN services for residential/business end-users and AIN queries for enhanced service providers form the supply network of our study. Profit maximizing models for each firm are formulated and solved using the mathematical programming software GAMS and the PATH module to obtain an equilibrium set of output and prices for the firms of the supply network.     

供应链管理环境下第三方物流企业的评价选择

现代企业的竞争已经转变为供应链之间的竞争,评价选择第三方物流企业是构建高效率供应链的重要一步。文章介绍了第三方物流企业的发展,提出了选择第三方物流企业的综合评价层次体系结构,详细阐述了一种集成AHP和模糊综合评价的方法评价选择第三方物流企业的步骤。     

System for supply network management

Strategies and algorithms for operational planning and control are quite important to successful operations of a supply network. Implementation of a strategy requires substantial information system support, but few detailed designs of such systems have appeared in the literature. We designed an information system for a centralized management concept that could handle any type of strategy or algorithm. We developed algorithms for two different strategies deemed important by researchers and practitioners, push and pull, and implemented them in system modules. This information system performed well in simulations of the management of operations of an example six-stage supply network. This system provides an example for operational development as well as a platform for laboratory experiments.