https://www.cirrelt.ca/DocumentsTravail/CIRRELT-2011-62.pdf

A review of dynamic vehicle routing problems

Innovation is one of the most important issues in business research today. It has been studied in many independent research traditions. Our understanding and study of innovation can benefit from an integrative review of these research traditions. In so doing, we identify 16 topics relevant to marketing science, which we classify under five research fields: - Consumer response to innovation, including attempts to measure consumer innovative-ness, models of new product growth, and recent ideas on network externalities - Organizations and innovation, which are increasingly important as product development becomes more complex and tools more effective but demanding - Market entry strategies, which includes recent research on technology revolution, exten-sive marketing science research on strategies for entry, and issues of portfolio manage-ment - Prescriptive techniques for product development processes, which have been transformed through global pressures, increasingly accurate customer input, web-based communica-tion for dispersed and global product design, and new tools for dealing with complexity over time and across product lines - Defending against market entry and capturing the rewards of innovating, which includes extensive marketing science research on strategies of defense, managing through metrics and rewards to entrants For each topic, we summarize key concepts and highlight research challenges. For pre-scriptive research topics, we also review current thinking and applications. For descriptive top-ics, we review key findings.

Research on Innovation: A Review and Agenda for Marketing Science

The multiple traveling salesman problem (mTSP) is a generalization of the well-known traveling salesman problem (TSP), where more than one salesman is allowed to be used in the solution. Moreover, the characteristics of the mTSP seem more appropriate for real-life applications, and it is also possible to extend the problem to a wide variety of vehicle routing problems (VRPs) by incorporating some additional side constraints. Although there exists a wide body of the literature for the TSP and the VRP, the mTSP has not received the same amount of attention. The purpose of this survey is to review the problem and its practical applications, to highlight some formulations and to describe exact and heuristic solution procedures proposed for this problem.

The multiple traveling salesman problem : an overview of formulations and solution procedures

Complexity and Approximation

Innovation is one of the most important issues in business research today. It has been studied in many independent research traditions. Our understanding and study of innovation can benefit from an integrative review of these research traditions. In so doing, we identify 16 topics relevant to marketing science, which we classify under five research fields:


Consumer response to innovation, including attempts to measure consumer innovativeness, models of new product growth, and recent ideas on network externalities; Organizations and innovation, which are increasingly important as product development becomes more complex and tools more effective but demanding;.
Market entry strategies, which includes recent research on technology revolution, extensive marketing science research on strategies for entry, and issues of portfolio management;
Prescriptive techniques for product development processes, which have been transformed through global pressures, increasingly accurate customer input, Web-based communication for dispersed and global product design, and new tools for dealing with complexity over time and across product lines;
Defending against market entry and capturing the rewards of innovating, which includes extensive marketing science research on strategies of defense, managing through metrics, and rewards to entrants.



For each topic, we summarize key concepts and highlight research challenges. For prescriptive research topics, we also review current thinking and applications. For descriptive topics, we review key findings.

/pdf/research-on-innovation-a-review-and-agenda-for-marketing-3tl8dfo5vf.pdf

The dynamic Pickup and Delivery Problem with Time Windows (PDPTW) is faced by courier companies serving same-day pickup and delivery requests for the transport of letters and small parcels. This article focuses on the dynamic PDPTW for which future requests are not stochastically modelled or predicted. The standard solution methodology for the dynamic PDPTW is the use of a rolling time horizon as proposed by Psaraftis. When assigning a new request to a vehicle it may be preferable to consider the impact of a decision both on a short-term and on a long-term horizon. In particular, better managing slack time in the distant future may help reduce routing cost. This paper describes double-horizon based heuristics for the dynamic PDPTW. Computational results show the advantage of using a double-horizon in conjunction with insertion and improvement heuristics.

Double-horizon based heuristics for the dynamic pickup and delivery problem with time windows

A dynamic-programming heuristic is described to find approximate solutions to the problem of identifying a new, multi-attribute product profile associated with the highest share-of-choices in a competitive market. The input data consist of idiosyncratic multi-attribute preference functions estimated using conjoint or hybrid-conjoint analysis. An individual is assumed to choose a new product profile if he/she associates a higher utility with it than with a status-quo alternative. Importance weights are assigned to individuals to account for differences in their purchase and/or usage rates and the performance of a new product profile is evaluated after taking into account its cannibalization of a seller's existing brands. In a simulation with real-sized problems, the proposed heuristic strictly dominates an alternative lagrangian-relaxation heuristic in terms of both computational time and approximation of the optimal solution. Across 192 simulated problems, the dynamic-programming heuristic identifies product profiles whose share-of-choices, on average, are 98.2% of the share-of-choices of the optimal product profile, suggesting that it closely approximates the optimal solution.

A Heuristic Approach to Product Design

This paper shows that a minimization version of satisfiability is strongly NP-hard, even if each clause contains no more than two literals and/or each clause contains at most one unnegated variable. The worst-case and average-case performances of greedy and probabilistic greedy heuristics for the problem are examined, and tight upper bounds on the performance ratio in each case are developed.

The Minimum Satisfiability Problem

Optimal product design using conjoint analysis: Computational complexity and algorithms

The Multicast/Broadcast Service (MBS) feature of mobile WiMAX network is a promising technology for providing wireless multimedia, because it allows the delivery of multimedia content to large-scale user communities in a cost-efficient manner. In this paper, we consider WiMAX networks that transmit multiple video streams encoded in scalable manner to mobile receivers using the MBS feature. We focus on two research problems in such networks: 1) maximizing the video quality and 2) minimizing energy consumption for mobile receivers. We formulate and solve the substream selection problem to maximize the video quality, which arises when multiple scalable video streams are broadcast to mobile receivers with limited resources. We show that this problem is NP-Complete, and design a polynomial time approximation algorithm to solve it. We prove that the solutions computed by our algorithm are always within a small constant factor from the optimal solutions. In addition, we extend our algorithm to reduce the energy consumption of mobile receivers. This is done by transmitting the selected substreams in bursts, which allows mobile receivers to turn off their wireless interfaces to save energy. We show how our algorithm constructs burst transmission schedules that reduce energy consumption without sacrificing the video quality. Using extensive simulation and mathematical analysis, we show that the proposed algorithm: 1) is efficient in terms of execution time, 2) achieves high radio resource utilization, 3) maximizes the received video quality, and 4) minimizes the energy consumption for mobile receivers.

/pdf/energy-efficient-multicasting-of-scalable-video-streams-over-1kj4t1l65w.pdf

Ramesh Krishnamurti

Papers

Double-horizon based heuristics for the dynamic pickup and delivery problem with time windows

A Heuristic Approach to Product Design

The Minimum Satisfiability Problem

Optimal product design using conjoint analysis: Computational complexity and algorithms

Energy-Efficient Multicasting of Scalable Video Streams Over WiMAX Networks