A partial robust optimization approach to inventory management for the offline-to-online problem under different selling prices

This study examines an optimal inventory strategy when a retailer markets a product at different selling prices through a dual-channel supply chain, comprising an online channel and an offline channel. Using the operating pattern of the offline-to-online (O2O) business model, we develop a partial robust optimization (PRO) model. Then, we provide a closed-form solution when only the mean and standard deviation of the online channel demand distribution is known and the offline channel demand follows a uniform distribution (partial robust). Specifically, owing to the good structural properties of the solution, we obtain a heuristic ordering formula for the general distribution case (i.e., the offline channel demand follows a general distribution). In addition, a series of numerical experiments prove the rationality of our conjecture. Moreover, after comparing our solution with other possible policies, we conclude that the PRO approach improves the performance of incorporating the internet into an existing supply chain and, thus, is able to adjust the level of conservativeness of the solution. Finally, in a degenerated situation, we compare our PRO approach with a combination of information approach. The results show that the PRO approach has more “robust” performance. As a result, a reasonable trade-off between robustness and performance is achieved.     

GROUP SIZE AND PARALLELISM EFFECTS IN TASKS WITHHETEROGENEOUS LEVELS OF DIFFICULTY：A STOCHASTIC ORDER APPROACH

We consider tasks where in order to perform them it is sufficient that one member of a group will know how to do it. We are interested in the effect of task difficulty, and variability of that difficulty, on group performance, and in particular on the marginal contribution of an additional number to the performance of groups of different size. We explore the implications of various stochastic orders over task difficulty and variability. Some intuitive conjectures are shown to be false.     

GROUP-BUYING ONLINE AUCTION AND OPTIMAL INVENTORY POLICY IN UNCERTAIN MARKET

In this paper we consider a group-buying online auction (GBA) model for a monopolistic manufacturer selling novel products in the uncertain market. Firstly, we introduce the bidder's dominant strategy, after which we optimize the GBA price curve and the production volume together. Finally, we compare the GBA with the traditional posted pricing mechanism and find that the GBA is highly probable to be advantageous over the posted pricing mechanism in some appropriate market environments.     

AUTOMATIC DECISION-MAKING： NEURAL FIRING AND RESPONSE

1. Introduction This is the fourth exposition on theAnalytic Hierarchy Process. It is true thatmany decisions we make subconsciously ariseout of our physical and biological needs andderive from the pressure to survive physically.We also make subconsciou…     

THE PERIODIC CAPACITATED ARC ROUTING PROBLEM LINEAR PROGRAMMING MODEL, METAHEURISTIC AND LOWER BOUNDS

1. Introduction The Capacitated Arc Routing Problem(CARP) is defined on an undirected network inwhich a fleet of identical vehicles with limitedcapacity is based at a depot node. Each edge hasa non-negative traversal cost and can betraversed any number…     

STUDIES ON HORIZONTAL COMPETITION AMONG HOMOGENOUS RETAILERS THROUGH AGENT-BASED SIMULATION

1. Introduction A supply chain is a network composed osuppliers, manufacturers, retailers, etc., whichcooperate to offer a kind of goods or servicesThese supply chain members cooperate andcompete with each other to maximize theiown profits. For example,…     

Fundamentals of the analytic network process — Dependence and feedback in decision-making with a single network

The Analytic Network Process (ANP) is a multicriteria theory of measurement used to derive relative priority scales of absolute numbers from individual judgments (or from actual measurements normalized to a relative form) that also belong to a fundamental scale of absolute numbers. These judgments represent the relative influence, of one of two elements over the other in a pairwise comparison process on a third element in the system, with respect to an underlying control criterion. Through its supermatrix, whose entries are themselves matrices of column priorities, the ANP synthesizes the outcome of dependence and feedback within and between clusters of elements. The Analytic Hierarchy Process (AHP) with its independence assumptions on upper levels from lower levels and the independence of the elements in a level is a special case of the ANP. The ANP is an essential tool for articulating our understanding of a decision problem. One had to overcome the limitation of linear hierarchic structures and their mathematical consequences. This part on the ANP summarizes and illustrates the basic concepts of the ANP and shows how informed intuitive judgments can lead to real life answers that are matched by actual measurements in the real world (for example, relative dollar values) as illustrated in market share examples that rely on judgments and not on numerical data. Thomas L. Saaty holds the Chair of University Professor, Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, PA, and obtained his Ph.D. in mathematics from Yale University. Before that he was a professor at the Wharton School of the University of Pennsylvania for ten years. Prior to that he spent seven years at the Arms Control and Disarmament Agency in the State Department in Washington, DC, that carried out the arms reduction negotiations with the Soviets in Geneva. His current research interests include decision-making, planning, conflict resolution and synthesis in the brain. As a result of his search for an effective means to deal with weapons tradeoffs at the Disarmament Agency and, more generally, with decision-making and resource allocation, Professor Saaty developed The Analytic Hierarchy Process (AHP) and its generalization to dependence and feedback, the Analytic Network Process (ANP). He is co-developer of the software Expert Choice and of the software Super Decisions for decisions with dependence and feedback. He has authored or co-authored twelve books on the AHP/ANP. Professor Saaty has also written a number of other books that embrace a variety of topics, including Modern Nonlinear Equations, Nonlinear Mathematics, Graph Theory, The Four Color Problem, Behavioral Mathematics, Queuing Theory, Optimization in Integers, Embracing the Future and The Brain: Unraveling the Mystery of How It Works. His most recent book is Creative Thinking, Problem Solving & Decision Making. The book is a rich collection of ideas, incorporating research by a growing body of researchers and practitioners, profiles of creative people, projects and products, theory, philosophy, physics and metaphysics...all explained with a liberal dose of humor. He has published more than 300 refereed articles in a wide variety of professional journals. He has been on the editorial boards of Mathematical Reviews, Operations Research, Naval Research Logistics Quarterly, Mathematical and Computer Modeling, Socio-Economic Planning Sciences, Applied Mathematics Letters, and several others. He also served as consultant to many corporations and governments.     

ENTROPY,INFORMATION,NOISE—STUDIES ON SYSTEM EVOLUTION

Universe, ecosystem, social system, etc. are evolving systems. The evolving processes of thesesystems have gradual small changes and rapid drastic changes with uncertainties under the constraintsof environment. Systems, as a whole, are evolving toward complexity, diversity and variety withfluctuations and jumps. New order emerges from "mutations". The evolution is bothchance-dependent and path-dependent. In this paper three basics: entropy, information and noise areemphasized with regard to system evolution which is a field that can give people wisdom to solvesystem problems with domain knowledge.     

COMPARISON OF MAX—MIN APPROACH AND NN METHOD FOR RELIABILITY OPTIMIZATION OF SERIES—PARALLEL SYSTEM

Two heuristics, the max-min approach and the Nakagawa and Nakashima method, are consideredfor the redundancy allocation problem with series-parallel structure. The max-min approach canformulate the problem as an integer linear programming problem instead of an integer nonlinearproblem. This paper presents a comparison between those methods from the standpoint of solutionquality and computational complexity. The experimental results show that the max-min approach issuperior to the Nakagawa and Nakashima method in terms of solution quality in small-scale problems,but analysis of computational complexity shows that the max-min approach is inferior to other greedyheuristics.     

STABILITY CRITERIA FOR A CLASS OF UNCERTAINSYSTEMS WITH TIME—DELAY

Some stability criteria are obtained for a class of uncertain systems with time-delay usingLyapunov functional and analytic techniques. It is easy to check the criteria by making use of theboundedness of the uncertainties.