The design of a controller in Fuzzy Petri net

This paper designs a class of Fuzzy Petri net controller based on the character of place invariant in Petri net. This controller is simple in operation and is easy to put into practice. It has satisfying effects and can provide methods to do research in designing and optimizing the performance of system in solving the dead lock phenomenon in concurrent system.     

A Petri net approach to the modelling and analysis of flexible manufacturing systems

In this paper we present an approach for modelling and analyzing flexible manufacturing systems (FMSs) using Petri nets. In this approach, we first build a Petri net model (PNM) of the given FMS in a bottom-up fashion and then analyze important qualitative aspects of FMS behaviour such as existence/absence of deadlocks and buffer overflows. The basis for our approach is a theorem we state and prove for computing the invariants of the union of a finite number of Petri nets when the invariants of the individual nets are known. We illustrate our approach using two typical manufacturing systems: an automated transfer line and a simple FMS.A shorter version of this paper was presented at the 1st ORSA/TIMS Special Interest Conference on FMSs, University of Michigan, Ann Arbor, August 1984.     

Scheduling of piecewise constant product flows: A Petri net approach

Scheduling a manufacturing system is usually an NP-hard problem. This means that only heuristic algorithms can be used to provide near-optimal schedules. In this paper, we show that a manufacturing system can be modeled using a particular type of Petri nets, called Controllable-Output nets, or CO nets for short. These Petri net models are then used to introduce a two-stage scheduling algorithm for problems in which the product flows can be considered as piecewise constant. The first stage consists of distributing the workload among the resources. The second stage derives a schedule from the resource workload. The deterministic case is considered. Numerical results are proposed.     

Synchronization in supply chains: implications for design and management

Supply chain management literature calls for coordination between the different members of the chain. Materials should be moved from one supplier to the next according to a just-in-time schedule. In this paper, we show that for many supply chain configurations, complete synchronization will result in some members of the chain being ‘losers’ in terms of cost. We develop an algorithm for optimal synchronization of supply chains and provide some guidelines for incentive alignment along the supply chain. In developing the model, we use the economic delivery and scheduling problem model and analyze supply chains dealing with single and multiple components. For single-component supply chains, we derive a closed-form expression for the optimal synchronized cycle time. For multi-component supply chains, we develop an algorithm for finding the optimal synchronized cycle time. We test the performance of the algorithm and show that it provides optimal solutions for a wide range of problems. We illustrate the models with numerical examples.     

Modeling and analysis of build-to-order supply chains

The build-to-order supply chain (BTO-SC) or make-to-order (MTO) system has received a great deal of attention in recent years because of the success of high-tech companies such as Dell, BMW, Compaq, and Gateway. Some auto companies have also implemented BTO-SC. Quite a few research articles have been written on BTO-SC and MTO. However, those that explicitly address the problems of BTO-SCM with modeling are rather limited in number. Considering the growing importance of more informed and timely decision making in these areas, there is a need to encourage further research on the modeling and analysis of global outsourcing, optimization between product variants and the cost of production, the point of differentiation along the production/assembly process, the selection of suppliers, logistics costs, and customer relationship management. Traditional operations research models have been used to solve supply chain management problems. Considering the importance of BTO or MTO, an attempt has been made to review the selected literature on the modeling and analysis of BTO-SC with the objectives of providing assistance to and motivating both researchers and practitioners to design, develop, and manage BTO-SC effectively; and suggesting some future research directions on BTO supply chain management (BTO-SCM). The literature available on BTO-SCM has been classified based on the nature of the decision-making areas and then sub-classified to focus on solving problems with modeling and analysis. We have focused mostly on the modeling aspect of the BTO-SC, but have not extended our efforts to empirical research. We have developed a unified framework for modeling and analyzing BTO-SCM and suggest some future research directions.     

Integrated modeling of extended agro-food supply chains: A systems approach

The current intense food production-consumption is one of the main sources of environmental pollution and contributes to anthropogenic greenhouse gas emissions. Organic farming is a potential way to reduce environmental impacts by excluding synthetic pesticides and fertilizers from the process. Despite ecological benefits, it is unlikely that conversion to organic can be financially viable for farmers, without additional support and incentives from consumers. This study models the interplay between consumer preferences and socio-environmental issues related to agriculture and food production. We operationalize the novel concept of extended agro-food supply chain and simulate adaptive behavior of farmers, food processors, retailers, and customers. Not only the operational factors (e.g., price, quantity, and lead time), but also the behavioral factors (e.g., attitude, perceived control, social norms, habits, and personal goals) of the food suppliers and consumers are considered in order to foster organic farming. We propose an integrated approach combining agent-based, discrete-event, and system dynamics modeling for a case of wine supply chain. Findings demonstrate the feasibility and superiority of the proposed model over the traditional sustainable supply chain models in incorporating the feedback between consumers and producers and analyzing management scenarios that can urge farmers to expand organic agriculture. Results further indicate that demand-side participation in transition pathways towards sustainable agriculture can become a time-consuming effort if not accompanied by the middle actors between consumers and farmers. In practice, our proposed model may serve as a decision-support tool to guide evidence-based policymaking in the food and agriculture sector.     

Cost analysis in global supply chains

This paper aims to explore effect of supply chain members’ costs change on participants of the network. On one perspective, it explores when there is a cost change to a firm, how other firms are affected and who bear(s) the most effect. On the other perspective, it investigates how an individual firm’s performance is affected by the other members in its network and whose cost change would impose a most significant effect on its profit.     

An analytical method for cost analysis in multi-stage supply chains: A stochastic network model approach

This paper studies the cost distribution characteristics in multi-stage supply chain networks. Based on the graphical evaluation and review technique, we propose a novel stochastic network mathematical model for cost distribution analysis in multi-stage supply chain networks. Further, to investigate the effects of cost components, including the procurement costs, inventory costs, shortage costs, production costs and transportation costs of supply chain members, on the total supply chain operation cost, we propose the concept of cost sensitivity and provide corresponding algorithms based on the proposed stochastic network model. Then the model is extended to analyze the cost performance of supply chain robustness under different order compensation ability scenarios and the corresponding algorithms are developed. Simulation experiment shows the effectiveness and flexibility of the proposed model, and also promotes a better understanding of the model approach and its managerial implications in cost management of supply chains.     

Methodological analysis of supply chains management applications

Formal modelling may be used to express management operational plans to achieve the desired normative objectives of firms. The plans so formulated should be demonstrably optimal with regard to certain specific objectives assumed by top management and ought to provide accurate results, when enacted, with a given tolerance at a prespecified probability.     

An optimization-based approach to assess non-interference in labeled and bounded Petri net systems

An optimization-based approach to assess both strong non-deterministic non- interference (SNNI) and bisimulation SNNI (BSNNI) in discrete event systems modeled as labeled Petri nets is presented in this paper. The assessment of SNNI requires the solution of feasibility problems with integer variables and linear constraints, which is derived by extending a previous result given in the case of unlabeled net systems. Moreover, the BSNNI case can be addressed in two different ways. First, similarly to the case of SNNI, a condition to assess BSNNI, which is necessary and sufficient, can be derived from the one given in the unlabeled framework, requiring the solution of feasibility problems with integer variables and linear constraints. Then, a novel necessary and sufficient condition to assess BSNNI is given, which requires the solution of integer feasibility problems with nonlinear constraints. Furthermore, we show how to recast these problems into equivalent mixed-integer linear programming (MILP) ones. The effectiveness of the proposed approaches is shown by means of several examples. It turns out that there are relevant cases where the new condition to assess BSNNI that requires the solution of MILP problems is computationally more efficient, when compared to the one that requires the solution of feasibility problems.     

A flexible and generic approach to dynamic modelling of supply chains

In this paper, we present a new modelling approach for realistic supply chain simulation. The model provides an experimental environment for informed comparison between different supply chain policies. A basic simulation model for a generic node, from which a supply chain network can be built, has been developed using an object-oriented approach. This generic model allows the incorporation of the information and physical systems and decision-making policies used by each node. The object-oriented approach gives the flexibility in specifying the supply chain configuration and operation decisions, and policies. Stochastic simulations are achieved by applying Latin Supercube Sampling to the uncertain variables in descending order of importance, which reduces the number of simulations required. We also present a case study to show that the model is applicable to a real-life situation for dynamic stochastic studies.     

Integrated design and operation of remnant inventory supply chains under uncertainty

We consider the simultaneous design and operation of remnant inventory supply chains. Remnant inventory is generated when demand for various lengths of a product may be satisfied by existing inventory, or by cutting a large piece into smaller pieces. We formulate our problem as a two-stage stochastic mixed-integer program. In solving our stochastic program, we enhance the standard L-shaped method in two ways. Our computational experiments demonstrate that these enhancements are effective, dramatically reducing the solution time for large instances.     

A method to abstract a stochastic Petri net

We propose a method to abstract a given stochastic Petri net (SPN). We shall show that the reachability tree of the given SPN is isomorphic to a Markov renewal process. Then, the given SPN is transformed to a state transition system (STS) and the STS is reduced. The reduction of states on STS corresponds to a fusion of series transitions on the SPN. The reduced STS is again transformed to an abstract SPN. We show that it is helpful to use the notion of the conditional firstpassage time from a certain state to the others on the STS to reduce nonessential states, thus places and transitions on the given SPN. Mass functions, that is, the distribution functions of conditional first-passage time between preserved states on the reduced MRP, preserve firing probabilities of fused transitions. Firing probability of the preserved transition also preserves the stochastic properties of the fused transitions.     

Coordination of supply chains by option contracts: A cooperative game theory approach

Manufacturer–retailer supply chains commonly adopt a wholesale price mechanism. This mechanism, however, has often led manufacturers and retailers to situations of conflicts of interest. For example, due to uncertain market demand, retailers prefer to order flexibly from manufacturers so as to avoid incurring inventory costs and to be able to respond flexibly to market changes. Manufacturers, on the other hand, prefer retailers to place full orders as early as possible so that they can hedge against the risks of over- and under-production. Such conflicts between retailers and manufacturers can result in an inefficient supply chain. Motivated by this problem, we take a cooperative game approach in this paper to consider the coordination issue in a manufacturer–retailer supply chain using option contracts. Using the wholesale price mechanism as a benchmark, we develop an option contract model. Our study demonstrates that, compared with the benchmark based on the wholesale price mechanism, option contracts can coordinate the supply chain and achieve Pareto-improvement. We also discuss scenarios in which option contracts are selected according to individual supply chain members’ risk preferences and negotiating powers.     

Closed-loop supply chain network design: A financial approach

The more common approaches used in the SCM consider only the physical logistic operations and ignore the financial aspects of the chain. This paper presents a financial approach to model a closed-loop supply chain design in which financial aspects are explicitly considered as exogenous variables. The model decides to determine the strategic decisions as well as the tactical decisions. The main contribution of this paper is to incorporate the financial aspects (i.e. current and fixed assets and liabilities) and a set of budgetary constraints representing balances of cash, debt, securities, payment delays, and discounts in the supply chain planning. Moreover, the financial approach applies the change in equity (instead of the measure of profit/cost in traditional approaches) as the objective function to be optimized in the presented model.To show the advantages of the presented approach, the results attributed to the financial approach and the traditional approach are compared, where the latter firstly decides on operations and fits finances afterwards. The results indicate that the traditional approach leads to lower change in equity compared to the financial approach. This fact illustrates the inadequacy of treating process operations and finances in isolated environments and pursuing as objective myopic performance indicators such as profit or cost. Moreover, a sensitivity analysis of the parameters using ANOVA for different levels of the parameters under different customer order patterns is performed to enhance the managerial insights of the study. The results clearly reveal the better improvement of using the financial approach over the traditional approach, and convince the decision makers to take advantage of the proposed approach.     

Surplus division and investment incentives in supply chains: A biform-game analysis

In this paper, we use a biform-game approach for analyzing the impact of surplus division in supply chains on investment incentives. In the first stage of the game, firms decide non-cooperatively on investments. In the second stage, the surplus is shared according to the Shapley value. We find that all firms have inefficiently low investment incentives which, however, depend on their position in the supply chain. Cross-subsidies for investment costs can mitigate, but not eliminate the underinvestment problem. Vertical integration between at least some firms.yields efficient investments, but may nevertheless reduce the aggregated payoff of the firms. We show how the size of our effects depends on the structure of the supply chain and the efficiency of the investment technology. Various extensions demonstrate that our results are qualitatively robust.     

Simultaneous design and planning of supply chains with reverse flows: A generic modelling framework

The increase in societal awareness towards environmental issues has accrued the responsibility of goods producers, which at present came to encompass the entire product life cycle. Recently, the efficient design and operation of supply chains with return flows have, in particular, become a major challenge for many companies, given the high number of factors involved and their intricate interactions.     

Optimizing of bullwhip effect and net stock amplification in three-echelon supply chains using evolutionary multi-objective metaheuristics

In this article, we intend to model and optimize the bullwhip effect (BWE) and net stock amplification (NSA) in a three-stage supply chain consisting of a retailer, a wholesaler, and a manufacturer under both centralized and decentralized scenarios. In this regard, firstly, the causes of BWE and NSA are mathematically formulated using response surface methodology (RSM) as a multi-objective optimization model that aims to minimize the BWE and NSA on both chains. The simultaneous analysis of the BWE and NSA is considered as the main novelty of this paper. To tackle the addressed problem, we propose a novel multi-objective hybrid evolutionary approach called MOHES; MOHES is a hybrid of two known multi-objective algorithms i.e. multi-objective electro magnetism mechanism algorithm (MOEMA) and population-based multi-objective simulated annealing (PBMOSA). We applied a co-evolutionary strategy for this purpose with eligibility of both algorithms. Proposed MOHES is compared with three common and popular algorithms (i.e. NRGA, NSGAII, and MOPSO). Since the utilized algorithms are very sensitive to parameter values, RSM with the multi-objective decision making (MODM) approach is employed to tune the parameters. Finally, the hybrid algorithm and the singular approaches are compared together in terms of some performance measures. The results indicate that the hybrid approach achieves better solutions when compared with the others, and also the results show that in a decentralized chain, the order batching factor and the demand signal processing in wholesaler are the most important factors on BWE. Conversely, in a centralized chain, factors such as rationing, shortage gaming, and lead time are the most effective at reducing the BWE.     

Modeling of a discrete dynamic system using a modified Petri net

Together with the proposed modification connected with the introduction of a time-dependent net, we define a criterion for optimality of a sequence of initiations of transitions, and study a method of obtaining such a sequence. We given the construction of a model of a discrete dynamic system having finite parameters. to describe it we introduce a modification of the Petri net using a determination of the state of the positions, time delay of the transitions, and variation of the conditions and rules for initiating transitions. Translated fromDinamicheskie Sistemy, No. 13, 1994. pp. 39–50.     

An integrated guaranteed- and stochastic-service approach to inventory optimization in supply chains

Multi-echelon inventory optimization literature distinguishes stochastic- (SS) and guaranteed-service (GS) approaches as mutually exclusive frameworks. While the GS approach considers flexibility measures at the stages to deal with stockouts, the SS approach only relies on safety stock. Within a supply chain, flexibility levels might differ between stages rendering them appropriate candidates for one approach or the other. The existing approaches, however, require the selection of a single framework for the entire supply chain instead of a stage-wise choice. We develop an integrated hybrid-service (HS) approach which endogenously determines the overall cost-optimal approach for each stage and computes the required inventory levels. We present a dynamic programming optimization algorithm for serial supply chains that partitions the entire system into subchains of different types. From a numerical study we find that, besides implicitly choosing the better of the two pure frameworks, whose cost differences can be considerable, the HS approach enables additional pipeline and on-hand stock cost savings. We further identify drivers for the preferability of the HS approach.