Search

• Inventory games and carbon emissions in multi-echelon supply chains are studied. • Cost and emissions reduction are achieved by synchronizing the ordering cycles. • An algebraic method is used to find solutions for vertical cooperation. • The models are developed under the carbon tax policy. • The effect of the carbon tax on cost, emissions, and cooperation savings are examined. This paper studies carbon tax policy in inventory games of multi-echelon supply chains. Four structures are considered with regard to the decision-making of supply chain members (decentralized, vertical downward cooperation, vertical upward cooperation, and horizontal cooperation). The purposes are to find the solutions of inventory games at each cooperation scheme, to compare strategies, and to examine the impact of the carbon tax on costs, emissions, and cooperation savings. A coordination mechanism with synchronized cycles is proposed, using cooperative game theory concepts in SC centralization. Closed-form equilibrium values were calculated for the optimal replenishment cycles, costs, and carbon emissions functions. For this intent, an algebraic method was deployed for vertical cooperation games. Though, other games were solved by an exact solution method. The numerical examples examined the impacts of the carbon tax on each structure and compared optimal solutions. Moreover, the impact of inventory and carbon emissions parameters on the cost and carbon emissions savings from cooperation settings were evaluated, indicating that SCs can reduce both costs and carbon emissions through cooperation. Additionally, it was found that the carbon tax can reduce the level of carbon emissions, while simultaneously decreasing coalition costs and emissions savings. [ABSTRACT FROM AUTHOR]

Production costs in general, and workforce and inventory costs in particular, constitute a large fraction of the operating costs of many manufacturing plants. We introduce cooperative aggregate production planning as a way to decrease these costs. That is, when production planning of two or more facilities (plants) is integrated, they can interchange workforce and products inventory; thus, their product demands can be satisfied at lower cost. This paper quantifies the cost saving and synergy of different coalitions of production plants by a new linear model for cooperative aggregate planning problem. The developed approach is explicated with a numerical example in which inventory and workforce levels of different coalitions of facilities are evaluated. Afterward, a key question would be how the cost saving of a coalition should be divided among members. We tackle the problem using different methods of cooperative game theory. These methods are implemented in the numerical example to gain an insight into properties of the corresponding game results. [ABSTRACT FROM AUTHOR]

Sustainability is one of the most significant problems in today's world and the concept of sustainable development is being an important objective in construction projects. Since the large projects have enormous and different activities that should be scheduled by considering resource constraint and precedence relationship between them, the resource-constrained project scheduling problem (RCPSP) is a NP-hard problem. In this study, fuzzy project scheduling model is presented to solve RCPSP under uncertainty in availability of the resources and activities duration simultaneously. Subcontractors have incentive to share their resources in the form of coalition in order to reduce activities time and cost. In this research, cooperative game methods are introduced for fair allocating utility of the project, as well as, present supper-additivity, stability and satisfaction level of each coalition. Finally, sustainability concept is analyzed in RCPSP and cooperation of subcontractors in a coalition form, whereas in the previous researches these topics addressed separately or generally in project scheduling to minimize the makespan and maximize the profit of project. The results of the proposed model indicate that the subcontractors can obtain more profit and the balance between sustainability indicators in project management arises by collaboration. [ABSTRACT FROM AUTHOR]

• Transmission and maintenance departments cooperate to follow UN sustainability goals. • Sustainability management of water distribution network by cooperative game theory. • Network dynamic zoning through cooperative game theory during privatization. • Non-linear mixing of qualitative and quantitative factors in network utilities. • Fair operation and income sharing of water distribution network (WDN). Sustainability approaches in transmission and maintenance planning of network utilities with different maintenance zones, which involve increasing the reliability of the transfer while employing maintenance teams fairly, pose decision-making challenges. For these utilities, the best model to employ is the maximum-flow model, which considers network reliability and destination stocks. Therefore, the crucial point is to understand how zone owners can cooperate to maximize reliable transmission and increases maintenance income while considering fairness in allocating maintenance teams to maintenance centers over several periods. A Mixed-Integer Nonlinear Programming (MINLP) model is presented in this paper for maximizing the reliability in network utility issues, allocating maintenance teams, and exploring edge statuses. Cooperative Transmission and Maintenance (CTM) planning is a dynamic, multi-duration decision-making problem. The problem scale in this study is significantly enlarged to separate the lines into active, inactive, and in-repair sets, and consequently, a genetic algorithm is proposed. This study examines these approaches and analyses them (including collaborative outputs and managerial insights) in the context of three major water pipeline zones. Based on sensitivity analysis for 81 collaborative scenarios, the highest and lowest synergies were 83.61% and 36.7%, respectively. Finally, several collaborative income-sharing strategies based on game theory are investigated. [ABSTRACT FROM AUTHOR]

This study investigates a multiowner maximum-flow network problem, which suffers from risky events. Uncertain conditions effect on proper estimation and ignoring them may mislead decision makers by overestimation. A key question is how self-governing owners in the network can cooperate with each other to maintain a reliable flow. Hence, the question is answered by providing a mathematical programming model based on applying the triangular reliability function in the decentralized networks. The proposed method concentrates on multiowner networks which suffer from risky time, cost, and capacity parameters for each network’s arcs. Some cooperative game methods such as τ-value, Shapley, and core center are presented to fairly distribute extra profit of cooperation. A numerical example including sensitivity analysis and the results of comparisons are presented. Indeed, the proposed method provides more reality in decision-making for risky systems, hence leading to significant profits in terms of real cost estimation when compared with unforeseen effects. [ABSTRACT FROM AUTHOR]

Highlights • Using geographical location in distance matrixes cause extra optimization process. • The result of solved mixed integer programing is the input for metaheuristics. • Ant colony algorithm is selected metaheuristic for applying in promotion stage. • Horizontal collaboration of suppliers would lead to cost saving for these agents. • Shapley value and tau value are reliable payoff sharing technique for the problem. Abstract The impact of the horizontal collaboration of logistic providers as upstream supply chain elements is studied in this paper. The logistic providers can be considered as different players and, in order to analyze different types of coalitions by computing the synergy between the players in each cooperative structure, we developed a mixed integer programming (MIP) formulation for a cooperative inventory routing problem (Co-IRP). In this paper, each player has one depot and some retailers, which are considered as its available market. The model will have a many-to-many network structure once a coalition is formed, where a single product from different depots will be delivered to different retailers. We establish a robust version of Co-IRP, which is called Co-RIRP, considering uncertainty in the network. We developed a few metaheuristic algorithms to promote the gained results once MIP is solved. Finally, in order to share the possible cost saving between players and compare the assignments, we applied a few payoff distribution methods. In addition, a comprehensive analysis of example results and some important managerial insights are presented. [ABSTRACT FROM AUTHOR]