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Diptendu Chatterjee

Publications and source records attributed to Diptendu Chatterjee.

6 recordsLinked to original sources

A Graph Matching Based Approach for the Multi-Depot Capacitated Vehicle Routing Problem

The Multi-Depot Capacitated Vehicle Routing Problem (MDCVRP) asks for minimum-cost delivery tours from several capacitated depots to a set of customers. Like most vehicle-routing variants it is NP-hard, so practical solvers must trade solution quality against speed. We revisit this trade-off through the lens of graph matching. Adapting a matching-based construction first developed for the Traveling Tournament Problem, we present two algorithms, Cluster-First and Match-First, that reduce routing to a sequence of minimum-weight matchings. This is more than a heuristic. We prove that for tours of up to two targets the matching formulation solves the MDCVRP exactly in polynomial time for any number of depots, and that both algorithms are constant-factor approximations, with a tight factor of two, in the structured regimes. This matching optimum coincides with the exact combinatorial-auction optimum, so the auction serves as a strong quality baseline. On instances of 1000 customers and 20 depots our methods match or slightly beat that baseline in tour length while running two to three orders of magnitude faster, in tens of milliseconds against tens of seconds, a scale at which exact and auction-based solvers become impractical. Because Cluster-First routes each depot independently, the approach also re-routes cheaply when new customers arrive.

cs.DS

ScaloWork: Useful Proof-of-Work with Distributed Pool Mining

Bitcoin blockchain uses hash-based Proof-of-Work (PoW) that prevents unwanted participants from hogging the network resources. Anyone entering the mining game has to prove that they have expended a specific amount of computational power. However, the most popular Bitcoin blockchain consumes 175.87 TWh of electrical energy annually, and most of this energy is wasted on hash calculations, which serve no additional purpose. Several studies have explored re-purposing the wasted energy by replacing the hash function with meaningful computational problems that have practical applications. Minimum Dominating Set (MDS) in networks has numerous real-life applications. Building on this concept, Chrisimos [TrustCom '23] was proposed to replace hash-based PoW with the computation of a dominating set on real-life graph instances. However, Chrisimos has several drawbacks regarding efficiency and solution quality. This work presents a new framework for Useful PoW, ScaloWork, that decides the block proposer for the Bitcoin blockchain based on the solution for the dominating set problem. ScaloWork relies on the property of graph isomorphism and guarantees solution extractability. We also propose a distributed approach for calculating the dominating set, allowing miners to collaborate in a pool. This enables ScaloWork to handle larger graphs relevant to real-life applications, thereby enhancing scalability. Our framework also eliminates the problem of free-riders, ensuring fairness in the distribution of block rewards. We perform a detailed security analysis of our framework and prove our scheme as secure as hash-based PoW. We implement a prototype of our framework, and the results show that our system outperforms Chrisimos in all aspects.

cs.CR

Chrisimos: A useful Proof-of-Work for finding Minimal Dominating Set of a graph

Hash-based Proof-of-Work (PoW) used in the Bitcoin Blockchain leads to high energy consumption and resource wastage. In this paper, we aim to re-purpose the energy by replacing the hash function with real-life problems having commercial utility. We propose Chrisimos, a useful Proof-of-Work where miners are required to find a minimal dominating set for real-life graph instances. A miner who is able to output the smallest dominating set for the given graph within the block interval time wins the mining game. We also propose a new chain selection rule that ensures the security of the scheme. Thus our protocol also realizes a decentralized minimal dominating set solver for any graph instance. We provide formal proof of correctness and show via experimental results that the block interval time is within feasible bounds of hash-based PoW.

cs.CR

Firefighter Problem with Minimum Budget: Hardness and Approximation Algorithm for Unit Disk Graphs

Unit disk graphs are the set of graphs which represent the intersection of disk graphs and interval graphs. These graphs are of great importance due to their structural similarity with wireless communication networks. Firefighter problem on unit disk graph is interesting as it models the virus spreading in an wireless network and asks for a solution to stop it. In this paper, we consider the MIN-BUDGET firefighter problem where the goal is to determine the minimum number of firefighters required and the nodes to place them at each time instant to save a given set of vertices of a given graph and a fire breakout node. We show that, the MIN-BUDGET firefighter problem in a unit disk graph is NP-Hard. We also present a constant factor approximation algorithm.

cs.DS

Complexity of Traveling Tournament Problem with Trip Length More Than Three

The Traveling Tournament Problem is a sports-scheduling problem where the goal is to minimize the total travel distance of teams playing a double round-robin tournament. The constraint 'k' is an imposed upper bound on the number of consecutive home or away matches. It is known that TTP is NP-Hard for k=3 as well as k=infinity. In this work, the general case has been settled by proving that TTP-k is NP-Complete for any fixed k>3.

cs.CC

An Improved Scheduling Algorithm for Traveling Tournament Problem with Maximum Trip Length Two

The Traveling Tournament Problem(TTP) is a combinatorial optimization problem where we have to give a scheduling algorithm which minimizes the total distance traveled by all the participating teams of a double round-robin tournament maintaining given constraints. Most of the instances of this problem with more than ten teams are still unsolved. By definition of the problem the number of teams participating has to be even. There are different variants of this problem depending on the constraints. In this problem, we consider the case where number of teams is a multiple of four and a team can not play more than two consecutive home or away matches. Our scheduling algorithm gives better result than the existing best result for number of teams less or equal to 32.

cs.DS