Partial Demand Information and Commitment in Dynamic Transportation Procurement

2020 ◽  
Vol 54 (3) ◽  
pp. 588-605
Author(s):  
Pol Boada-Collado ◽  
Sunil Chopra ◽  
Karen Smilowitz
Keyword(s):  
Partial Information ◽  
Planning Horizon ◽  
Decision Variable ◽  
Limited Information ◽  
Transportation Services ◽  
Capacity Level ◽  
Demand Information ◽  
Short Horizon ◽  
Procurement Contracts ◽  
Transportation Procurement

This paper analyzes a decision process of planning transportation procurement for a distribution lane given limited information regarding future demand for transportation services and a specified commitment horizon for procurement contracts. In contrast to variants in which either full demand information or no demand information is known over the planning horizon, our work considers the value of demand visibility for a short horizon in the future (i.e., the value of partial information). Our work also considers a commitment horizon that is much shorter than the planning horizon. We show that the availability of partial information fundamentally changes the contracting policies in the presence of such commitment horizons, and if used optimally, this information can be highly valuable. Partial visibility of demand can increase the willingness of the decision maker to commit to contracts and expand the range of capacity levels selected in settings where the capacity level of a contract is a decision variable. We also identify settings in which the value of partial information is negligible, reducing the incentive of managers to acquire additional demand information for future periods. Finally, we show that with seasonal demand, information is leveraged by properly coordinating with expected demand shocks (e.g., Black Friday) using tailored strategies.

SET-VALUED PERFORMANCE APPROXIMATIONS FOR THE QUEUE GIVEN PARTIAL INFORMATION

2020 ◽  
pp. 1-23
Author(s):  
Yan Chen ◽  
Ward Whitt
Keyword(s):  
Steady State ◽  
Decay Rate ◽  
Waiting Time ◽  
Partial Information ◽  
Upper And Lower Bounds ◽  
Interarrival Time ◽  
Limited Information ◽  
Wide Range ◽  
The Mean ◽  
Third Moment

In order to understand queueing performance given only partial information about the model, we propose determining intervals of likely values of performance measures given that limited information. We illustrate this approach for the mean steady-state waiting time in the $GI/GI/K$ queue. We start by specifying the first two moments of the interarrival-time and service-time distributions, and then consider additional information about these underlying distributions, in particular, a third moment and a Laplace transform value. As a theoretical basis, we apply extremal models yielding tight upper and lower bounds on the asymptotic decay rate of the steady-state waiting-time tail probability. We illustrate by constructing the theoretically justified intervals of values for the decay rate and the associated heuristically determined interval of values for the mean waiting times. Without extra information, the extremal models involve two-point distributions, which yield a wide range for the mean. Adding constraints on the third moment and a transform value produces three-point extremal distributions, which significantly reduce the range, producing practical levels of accuracy.

Effect of decision variable definition and data aggregation on a search process applied to a single-tree simulator

2001 ◽  
Vol 31 (6) ◽  
pp. 1057-1066 ◽  
Author(s):  
Peder Wikström
Keyword(s):  
Tabu Search ◽  
Data Aggregation ◽  
Net Present Value ◽  
Planning Horizon ◽  
Solution Technique ◽  
Search Process ◽  
Decision Variable ◽  
Stand Management ◽  
Harvest Timing ◽  
Execution Times

This paper focuses on how computer execution times and net present value (NPV) are affected by different groupings of tree-selection harvest controls, different procedures to determine harvest timing, and tree data aggregation. The problems related to stand management are viewed as a hierarchy, where the main problem is determining harvest periods and the subordinate problem is determining what trees to cut in a given set of harvest periods. The solution technique is a derivative-free search process, and the objective is to maximize the NPV of harvest revenues for a stand over a given planning horizon. The tree-selection harvest controls are based on diameter and species groupings. The procedure to determine harvest timing is based on Tabu search and fixed cutting cycles, respectively. Sensitivity analysis is performed for a selection of stands in southern Sweden, where each stand is represented by a set of inventoried plots. Both even-aged and uneven-aged management are considered. Solutions improved with the number of decision variables. The Tabu search procedure proved very efficient at determining harvest periods for the even-aged problems. For the uneven-aged problems, fixed cutting cycles approximated the harvest timing problem, but at considerably shorter execution times. It is suggested that aggregated data be used for determining harvest timing, after which, using the original nonaggregated data, the tree-selection problem for a given set of harvest periods can be resolved.

Inventory Replenishment for Profit Maximization over a Finite Horizon under One-time Cost Changes

2018 ◽  
Vol 19 (3_suppl) ◽  
pp. S235-S248
Author(s):  
F. J. Arcelus ◽  
T. P. M. Pakkala ◽  
G. Srinivasan
Keyword(s):  
Cost Minimization ◽  
Profit Maximization ◽  
Planning Horizon ◽  
Finite Horizon ◽  
Maximization Problem ◽  
Decision Variable ◽  
Time Cost ◽  
For Profit ◽  
Optimal Policies ◽  
The Cost

This article considers the optimal inventory ordering, purchasing and holding policies of the profit-maximization problem, as against the well-known cost-minimization case, over a finite horizon of length H, under two special conditions. First, there is change in at least one of the inventory costs, that is, in the cost of ordering and/or purchasing/holding, at some point, Tc < H, during the planning horizon. Second, it is not necessary to satisfy the demand, at a rate of R units per year, for the entire horizon. Rather, the objective is to meet the demand for a period of length H1 ≤ H. In fact, if the retailer does not have the obligation to meet the entire demand, this article shows the conditions wherein it may be more profitable to meet only a portion or may be even none of the demand. Further, such a determination can be made up front, with H1 as a decision variable and the optimal policies of the cost-minimization models, by fulfilling the entire demand, will result in lower profits. Numerical examples are included to identify the demand fulfilment and the profit differences between the cost-minimization and profit-maximization optimal policies, under the different one-time cost changes.

scholarly journals A Flexible Cap-and-Trade Policy and Limited Demand Information Effects on a Sustainable Supply Chain

2021 ◽  
Vol 13 (19) ◽  
pp. 10746
Author(s):  
Ying Gao ◽  
Jianteng Xu ◽  
Huixin Xu
Keyword(s):  
Trade Policy ◽  
Carbon Emission ◽  
Stackelberg Game ◽  
The Other ◽  
Limited Information ◽  
Low Carbon ◽  
Cap And Trade ◽  
Distribution Free ◽  
Demand Information ◽  
Limited Demand

Carbon emission reduction is increasingly becoming a public consensus, with governments formulating carbon emission policies, enterprises investing in emission abatement equipment, and consumers having a low-carbon preference. On the other hand, it is difficult for industry managers to obtain all the demand information. Based on this, this paper aims to investigate operations and coordination for a sustainable system with a flexible cap-and-trade policy and limited demand information. Newsvendor and distribution-free newsvendor models are formulated to show the validity of limited information. Stackelberg game is exploited to derive optimal abatement and order quantity solutions under centralized and decentralized systems. The revenue-sharing and two-part tariff contracts are then proposed to coordinate the decentralized system with limited demand information. Numerical analyses complement the theoretical results. We list some major findings. Firstly, we discover that using abatement equipment can effectively reduce emissions and increase profits. Secondly, the distribution-free approach is effective and acceptable for a system where only mean and variance information is informed. Thirdly, the mean parameter has a greater impact on profits and emissions comparing with the other seven parameters. Finally, we show that both contracts may achieve perfect coordination, and the two-part tariff contract is more robust.

A Framework for Analyzing Influencer Marketing in Social Networks: Selection and Scheduling of Influencers

2021 ◽  
Author(s):  
Rakesh R. Mallipeddi ◽  
Subodha Kumar ◽  
Chelliah Sriskandarajah ◽  
Yunxia Zhu
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Empirical Analysis ◽  
Big Data Analytics ◽  
Planning Horizon ◽  
Solution Procedure ◽  
Model Parameters ◽  
Exposure Effect ◽  
Social Media Platforms ◽  
Short Horizon

Explosive growth in the number of users on various social media platforms has transformed the way firms strategize their marketing activities. To take advantage of the vast size of social networks, firms have now turned their attention to influencer marketing wherein they employ independent influencers to promote their products on social media platforms. Despite the recent growth in influencer marketing, the problem of network seeding (i.e., identification of influencers to optimally post a firm’s message or advertisement) neither has been rigorously studied in the academic literature nor has been carefully addressed in practice. We develop a data-driven optimization framework to help a firm successfully conduct (i) short-horizon and (ii) long-horizon influencer marketing campaigns, for which two models are developed, respectively, to maximize the firm’s benefit. The models are based on the interactions with marketers, observation of firms’ message placements on social media, and model parameters estimated via empirical analysis performed on data from Twitter. Our empirical analysis discovers the effects of collective influence of multiple influencers and finds two important parameters to be included in the models, namely, multiple exposure effect and forgetting effect. For the short-horizon campaign, we develop an optimization model to select influencers and present structural properties for the model. Using these properties, we develop a mathematical programming based polynomial time procedure to provide near-optimal solutions. For the long-horizon problem, we develop an efficient solution procedure to simultaneously select influencers and schedule their message postings over a planning horizon. We demonstrate the superiority of our solution strategies for both short- and long-horizon problems against multiple benchmark methods used in practice. Finally, we present several managerially relevant insights for firms in the influencer marketing context. This paper was accepted by J. George Shanthikumar, big data analytics.

scholarly journals Implications for Firms with Limited Information to Take Advantage of Reference Price Effect in Competitive Settings

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Junhai Ma ◽  
Zhanbing Guo
Keyword(s):  
Reference Price ◽  
Partial Information ◽  
Necessary Condition ◽  
Adjustment Process ◽  
Flip Bifurcation ◽  
Limited Information ◽  
Dynamic Adjustment ◽  
Internal Reference ◽  
Special Cases ◽  
Price Effects

This paper studies internal reference price effects when competitive firms face reference price effects and make decisions based on partial information, where their decision-making mechanism is modeled by a dynamic adjustment process. It is shown that the evolution of this dynamic adjustment goes to stabilization if both adjustment speeds are small and the complexity of this evolution increases in adjustment speeds. It is proved that the necessary condition for flip bifurcation or Neimark-Sacker bifurcation will occur with the increase of adjustment speed in two special cases. What is more, numerical simulations show that these bifurcations do occur. Then, the impacts of parameters on stability and profits are investigated and some management insights for firms with limited information to take advantage of reference price effects are provided.

scholarly journals A Four-Type Decision-Variable MINLP Model for a Supply Chain Network Design

2010 ◽  
Vol 2010 ◽  
pp. 1-16 ◽  
Author(s):  
M. M. Monteiro ◽  
J. E. Leal ◽  
F. M. P. Raupp
Keyword(s):  
Supply Chain ◽  
Programming Model ◽  
Planning Horizon ◽  
Mixed Integer ◽  
Decision Variable ◽  
Abc Classification ◽  
Computational Implementation ◽  
Minlp Model ◽  
Nonlinear Programming Model ◽  
Outer Approximation Algorithm

We propose a mixed integer nonlinear programming model for the design of a one-period planning horizon supply chain with integrated and flexible decisions on location of plants and of warehouses, on levels of production and of inventory, and on transportation models, considering stochastic demand and the ABC classification for finished goods, which is an NP-hard industrial engineering optimization problem. Furthermore, computational implementation of the proposed model is presented through the direct application of the outer approximation algorithm on some randomly generated supply chain data.

scholarly journals Complexity Analysis of a Cournot-Bertrand Duopoly Game Model with Limited Information

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Hongwu Wang ◽  
Junhai Ma
Keyword(s):  
Complex Dynamics ◽  
Complexity Analysis ◽  
Mixed Duopoly ◽  
Decision Variable ◽  
Game Model ◽  
Limited Information ◽  
Nash Equilibrium Point ◽  
Route To Chaos ◽  
The One ◽  
Degree Of Differentiation

A Cournot-Bertrand mixed duopoly game model with limited information about the market and opponent is considered, where the market has linear demand and two firms have the same fixed marginal cost. The principles of decision-making are bounded rational. One firm chooses output and the other chooses price as decision variable, with the assumption that there is a certain degree of differentiation between the products offered by firms to avoid the whole market being occupied by the one that applies a lower price. The existence of Nash equilibrium point and its local stability of the game are investigated. The complex dynamics, such as bifurcation scenarios and route to chaos, are displayed using parameter basin plots by numerical experiment. The influences of the parameters on the system performance are discussed from the perspective of economics.

scholarly journals A Multiperiod Vehicle Lease Planning for Urban Freight Consolidation Network

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Woosuk Yang ◽  
Taesu Cheong ◽  
Sang Hwa Song
Keyword(s):  
Programming Model ◽  
Planning Horizon ◽  
Planning Problem ◽  
Transportation Services ◽  
Urban Freight ◽  
Urban Freight Transport ◽  
Freight Consolidation ◽  
Lagrangian Heuristic ◽  
Time Restriction

This paper considers a multiperiod vehicle lease planning problem for urban freight consolidation centers (UFCCs) in the urban freight transport network where short-term-leased and long-term-leased vehicles are hired together. The objective is to allocate the two kinds of leased vehicles optimally for direct transportation services from the associated origin node to the associated UFCC or from the associated UFCC to the associated destinations so as to satisfy a given set of period-to-period freight demands over a given planning horizon at total minimum vehicle allocation cost subject to demand-dependent transportation time restriction. The problem is formulated as an integer programming model and proven to be NP-hard in a strong sense. Thus, a Lagrangian heuristic is proposed to find a good solution efficiently. Numerical experiments show that the proposed algorithm finds good lower and upper bounds within reasonable time.

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